Assessment 1: Arranging for Ensemble Project Complete a 3-4-minute arrangement of a work originally for piano, organ or guitar, or a work that exists only as an audio recording (i.e. has no printed score). The arrangement should be for an ensemble of between 4 and 6 players. It may be any genre you like, but you must write for instruments available in your class. You will then rehearse and direct the arrangement in an informal performance which will be scheduled in the weeks following the score submission. Assessment Criteria Assessors will look for: Imaginative exploration of ensemble texture Idiomatic writing for instruments and/or voices Accuracy and attention to detail in the notation of a score and parts Clear and confident leadership of an ensemble in performance
29650 Engineering Mathematics 2 - Tutorial sheet 4 Question 1 A 4 state Markov model has states s1, s2, s3 and s4, initial state probability vector P 0 and transition probability matrix A given by (1) Questions: 1. Calculate the probability of the sequence s = s1s1s3s2s4s4 2. Calculate the state probability vectors P 1 and P 2 at times t = 1 and t = 2 respectively. Question 2 Two sequence generators X and Y output sequences of symbols a, b, c. They are modelled as 3 state Markov models MX and MY, respectively. MX has parameters (2) MY has parameters (3) In both cases the symbols a, b, c correspond to states 1, 2, 3 respectively. Generator X trans-mits signals 3 times more often than generator Y. Question: The sequence a, b, c is received. Which generator did it most probably come from? (Don’t forget what you learnt in the first three weeks of last Semester.... Bayes Theorem!) Question 3 I didn’t tell you how to do this in the lectures, but if you understand what a Markov process is it should be easy! A sequence generator X transmits the following sequences of symbols a, b: (4) Questions: 1. Use the sequences to estimate the parameters P0 and A of a 2 state Markov model of X. 2. Calculate P1, P2 and P3 3. Calculate limt→∞P t 4. Verify your answer by finding the eigenvalues and eigenvectors of AT. Question 4 A 3-state Markov process has parameters P0 and A given by: (5) State 3 is the exit state. A simple way to generate a random initial state from P0 is: 1. Generate a random number r uniformly distributed over [0, 1] 2. If r ≤ 0.7 output a else output b Having generated the first state the process continues as follows: 1. Choose the row of A corresponding to the current state s 2. Generate a random number r uniformly distributed over [0, 1] 3. If r ≤ as,1 output a, else if r ≤ as,1 + as,2 output b, else you have reached the exit state - don’t output anything - stop. 4. If the new state is state 3 then stop, else return to step 2. Questions: 1. What is the probability that the model generates a sequence of length exactly 2 symbols? 2. What is the value of Pt as t → ∞? 3. Use the following sequence of random numbers to generate as many sequences of out-puts a and b as possible from the model: 0.31, 0.53, 0.17, 0.6, 0.26, 0.65, 0.69, 0.75, 0.45, 0.08, 0.23, 0.91, 0.15, 0.83, 0.54, 0.99, 0.08, 0.44, 0.11, 0.96 4. Use the sequences that you have created to estimate the parameters of the Markov model that generated them. 5. How similar is this new model to the ‘correct’ model?
Fourier series (1) - tutorial questions It is not expected that you will complete all of these in the week they are released. Some can be used for revision practice. 1. Draw the graph of for 0 ≤ x ≤ 8 i.e. two periods 2. Draw the graph of What do you think the value of the Fourier series of f(x) is at x = 4 ? 3. What is the Fourier series of f(x) up to n = 3 f(x) = 2x 0 ≤ x ≤ 2π f(x + 2π) = f(x) 4. Find the Fourier series of 5. Find the Fourier series of 6. What is the Fourier series of f(x) = x2 0 ≤ x ≤ 2π f(x + 2π) = f(x) 7. Find the Fourier series of 8. Find the Fourier series of the following function (this is a difficult one)
ECO 202 (Section: LEC5101) Test 3 1. (15 pts) Below shows a hypothetical bank’s balance sheet: Column A Column B Loans x Deposits 2000 Investment 4000 Short-term Debt 1000 Cash and Reserves 100 Long-term Debt Net worth 2000 1100 Currently, the bank must maintain a reserve ratio of 5%. (a) (2 pts) Find the value of loans, x, under the column A. (b) (3 pts) What is this bank’s capital to asset ratio and reserve ratio? (c) (2 pts) Does the bank meet the capital requirement? (d) (4 pts) After a reform. in banking regulation, the bank is now required to meet a capital to asset ratio of 20% instead of the 5% reserve ratio. Does the bank meet his requirement? If so, what is the amount of excess capital held by the bank? If not, how much does the bank needs to augment its net worth by injecting more cash? (e) (4 pts) Calculate the leverage ratio. How much does the bank earn in term of percentage gain in net worth if the investment increase to 4200. 2. (15 pts) This question focuses on the IS model from Chapter 11. In a closed economy, the consumption (Ct), investment (It), and govern-ment purchases (Gt) are represented by the following equations: The C and G equations are the same as in the simple IS model, while the I equation includes an extension ¯xYet to capture the observation that more cash flow during an economic boom, leading to increased investment. (a) (2 pts) What is the expected range of the parameter ¯x? (b) (3 pts) Economists attribute the cost disadvantage of invest-ment using financing (i.e., borrowing) over cash flow to agency problems. List two types of agency problems and provide a brief explanation for each, using one to two sentences for each expla-nation. (c) (4 pts) Derive the IS curve. Must show all the important steps. (d) (3 pts) The economy is facing a recession where Ye = −10%. The government decided to implement a discretionary policy to boost the economy. By how much does the government need to change the ¯aG parameter? Show it with any relevant parameters. (e) (3 pts) Does the government need to spend more than the de-crease in output? Provide the intuition behind your answer with 3-4 sentences. 3. (10 pts) This question focus on the AS/AD model. Suppose that the aerospace industry develops a hydrogen-powered aeroplane, enabling ultra-low operating costs. This innovation leads to a one-time decrease in prices for the entire economy (i.e., ¯o < 0) for a single period, because of the reduced transportation costs to deliver around the globe. At the same time, household and firms are permissive about the future. These expectation shocks will persist until another exogenous change occurs. Assuming that the economy is initially in the steady state (i.e., π0 = ¯π and Yet = 0), answer the following questions using the AS/AD framework, specifying which parameters are changing. (a) (2 pts) Calculate the π1, the inflation right after the initial im-pact. Is π1 greater than π0? (b) (2 pts) Calculate the π2, the inflation as the economy is adjusting after the initial impact. Is π2 greater than π1? (c) (3 pts) Determine the initial impact of new invention on inflation and the output gap. Assume the impact on short-run output from AD is larger than that from the AS. Draw a graph to illustrate it (label all the axis and key points). (d) (3 pts) Determine the overall impact of new invention on infla-tion and the output gap. Draw a graph to illustrate it (label all the axis and key points). 4. (10 pts) As a policy advisor to the central bank with the objective of stabilizing inflation and economic activity, what would be your re-sponses to the following independent events? (a) (5 pts) Demand for Canadian lumber in the Japanese market has experienced a significant decline. (b) (5 pts) The government introduces a universal income program, which transfer money to every individual in the economy. This initiative is projected to incur higher government spending com-pared to all previous welfare programs combined. Assume no tax increase in the future.
IOM205 Advanced Database Management 1st SEMESTER 2025/26 Individual Coursework INSTRUCTIONS TO CANDIDATES 1. A single copy of your work must be submitted electronically through Learning Mall Online by 00:00, Monday, 15 Dec. 2025 (China Standard Time, UTC/ GMT+8). 2. This coursework will count for 70% of the final mark in this course. 3. Generative AI is not allowed in completing this coursework. Coursework Title: Individual Coursework: Implementing a Database using Microsoft Access Scenario: The Scenario is the same as GROUP COURSEWORK. Task Details/Description: For this coursework, you may continue working with the deliverables (ERM, Tables and Sample records) produced in the group coursework. Including any extra features, you may wish to – adding value to the application in functionality and usability may earn extra credit. Your report must clearly state these features. The primary task for this part ofthe coursework is to individually produce a fully tested and functional database application that has been implemented using Microsoft Access. Please note, you must at the minimum have the following functionalities in your database application to score a passing mark for the corresponding grading component. - Please refer to the pages at the end of this document for the grading components and criteria. Deliverables: You MUST submit the following two deliverables (ID1, 60% of total mark, and ID2, 40% of total mark) to complete this coursework. ID1: Fully tested and functional database that fulfils the functional requirements meeting the business needs specified in the scenario. • The database must support several business processes described in the scenario context and specification. You may change some of the design produced in the group coursework based on the feedback received from the instructors. • Include functionality (forms, queries, reports and charts) to support the main operations of the company. The database should be able to: add, edit and remove books, order books, generate invoices, reorder low stock and produce useful management information (e.g., total value of stocks). • Entities must be defined using a focused set of attributes that are both essential and contextually appropriate. Continue/revise on what has been produced in your group coursework. • Include at least one unbounded form, one trivial and one non-trivial form, that will help to realise key business needs, i.e., gather inputs and produce the correct output, which are user-friendly and displayed in an appropriate manner to the user (e.g., home page – unbounded form, add a new customer – trivial form, add new customer order, reorder books – non-trivial forms). • Include at least two non-trivial queries. Your queries should demonstrate the use of multiple tables, parameters, calculated fields and multi-stage query. You should also produce appropriate SQL code for at least one of your queries. The code should be annotated in the report to demonstrate your understanding (please refer to ID2.3 below in the deliverables section). • Include one neatly formatted Access report to provide useful management information. Include at least one level of grouping, and at least one summary/calculated field (e.g., customer invoice, most valued customer based on purchase orders, most popular books sold or reordered, total expenses incurred towards each publisher, most valued employee based on sales). • Include one Access chart linked to a form or report that illustrates some key operational information from the application to the organisation (e.g., sales made each month, popular books). ID2: Report not exceeding 1500 words (+/-10%), which MUST include the following. The front cover page (with student number and title of the assignment), table of contents, headers, sub-headers, figure and tables, labels as well as annotations, citations, and references, are not included in the word count (i.e., 1500 words). Estimated word limits for each section are provided below to help you write the report and have some idea of how much to focus on each section, while deciding the contents. You must use Harvard referencing style. for your references and citations. Please note, your report MUST include the following at a (or the) minimum to score a passing mark for the corresponding grading component. Please refer to the last two pages of this document for the grading components and criteria. • ID2.1: Simple instructions briefly describing how to operate the database. The instructions must be written as if for a typical employee with limited knowledge of Microsoft Access. You should use figures and annotate them to better articulate the instructions. Brief description of the core features (2 to 3) of the database, for example, how these features meet the needs of the business (e.g., useful non-trivial forms), addressing the current limitations, explained with the aid of screenshots from your database application (as applicable). Justify the features and/or design decisions citing appropriate literature. [estimated word limit — 300 words] • ID2.2: Include a concise description of one non-trivial form. that you designed. In your description [estimated word limit — 300 words]: • 1) specify why the form is non-trivial and how it addresses the organization’s needs. • 2) Provide figures or screenshots illustrating the form in table view, along with sample output. • ID2.3: Include a concise description of two non-trivial queries designed for management purposes. In your description [estimated word limit — 400 words]: • 1) specify why each query is non-trivial and how it addresses the organization’s needs. • 2) Provide figures or screenshots illustrating each query in table view, along with their corresponding output. • 3) You must also include the screenshot of the SQL code for both queries and briefly explain the code in your own words—demonstrating your understanding of how each query executes. • ID2.4: Include a brief description of one Access report. In your description, state why the report is useful for the management, and how it will add value to the business. Please include figures to show sample report outputs you have generated. [estimated word limit — 300 words]. Include a brief description of one non-trivial chart linked to a form. or report. Explain the value of the chart to the organisation. Please include a figure to show the sample output. You may annotate them (as applicable). [estimated word limit — 200 words] Submission: You are required to submit TWO files: (1) Your Microsoft Access Application (name_studentid.accdb); (2) Your Report (name_studentid.pdf/docx). The coursework is going to be submitted electronically. Further instructions about how to do this will be provided during a workshop session. Your work will be assessed on robustness, functionality meeting the business requirements, usability, and the overall quality of your design. The working and fully functional database will contribute to the majority weight for this coursework, hence please create necessary back-ups. Warning! If your database cannot be opened, is corrupt or is otherwise inaccessible, or your media contains malware, you will score ZERO for this part ofthe assignment. Please ensure you have created one or more back-up copies of your work in suitable places using appropriate mediums available to you, to avoid losing the work you may have already done. Assessment Weighting for the Module: The weight ofthe individual coursework is 70%
SOES6087: Key Skills in Global Marine Resources Management Assignment 1: Perform. an assessment of Habitat Suitability for the Manila Clam (Ruditapes philippinarum) in Southampton Water. The Manila Clam is an important fisheries species in the South of England. This assignment will allow you to carry out an assessment of Southampton Water for its suitability as a habitat using the Habitat Suitability Index (HSI) method. To be deemed suitable for Manila clam, this index should be greater than 0.5. Aim: This assignment is designed to test your data analysis skills. You will have to: summarise field data (LO6, LO8), write code to analyse this data (to create a Suitability Index (SI) model (LO4, LO6), and calculate the HSI (LO6)), present your data and results in a suitable format (LO3); consider uncertainty and error (LO4, LO6), and report your findings (LO3). A habitat suitability index (HSI) can be calculated for Ruditapes philippinarum, based on the weighted geometric mean of some easy to measure water quality and habitat variables (modifying the methods of Zeon et al., 2022): V1: Chlorophyll-a concentration (μg/L) V2: Near-bed flow velocity (m/s) V3: Sand (%) – assume this to be 50% and constant V4: Exposure time (hr) – assume subtidal conditions V5: Dissolved Oxygen (%) V6: Salinity (PSU) V7: Temperature (oC) For the listed variables, you will need to undertake the following steps: 1) Summarise the average values for observed variables (V1, V2, V5, V6, V7) within Southampton Water, during a defined field measurement period. 2) Using the MATLAB Live Script. model provided (HabitatSuitabilityIndex_Assessment.mlx), determine the Suitability Index for each of the parameters (V1 – V6). Create your own model for V7 by modifying the provided code. 3) Calculate the HSI, based on Equation 1, and the weighting factors provided. You may use any so ware you like to undertake this calculation. 4) Assess the variability of the variables measured, both individually and in combination. 5) Given the variability of your data determined in (4), design and carry out a sensitivity analysis for the HSI calculation. 6) Consider the longer-term variability of the parameters you have assessed (beyond the measurement period). You can do this from theory or literature. 7) Describe the uncertainty associated within your calculation. Calculation of the HSI is based on a weighted geometric mean, using the following equation: Eq. 1 Where Π indicates the product, V indicates the SI value for the variable, i is the variable index (1-7), and ω = weighting factor. Please see guidance notes at the end of this document if you are not familiar with applying this type of equation. The weighting factor for each variable is: Variable WeighⅥng Value (ω) V1 1 V2 10 V3 5 V4 2 V5 1 V6 1 V7 1 Write a report of no more than 6 pages* which summarises your assessment and answers the question: Is Southampton Water a suitable habitat for a Ruditapes philippinarum fishery. Your report should include: a. Introduction b. Data description/Methods c. Results – including suitable figures d. Discussion e. Conclusion f. References g. Appendix: including the group Cruise Report, and completed Matlab LiveScript. (*the appendix does not count towards the 6 page limit) You have limited space, so concentrate your figures on ones which illustrate your key findings (i.e. you do not have to recreate the SI figures you were provided with). References: Carter, M.C. 2003. Ruditapes philippinarum Manila clam. In Tyler-Walters H. and Hiscock K. Marine Life Information Network: Biology and Sensitivity Key Information Reviews, [on-line]. Plymouth: Marine Biological Association of the United Kingdom. [accessed: 15-08-2023]. Available from: htps://www.marlin.ac.uk/species/detail/2203 Smithsonian Environmental Research Centre. Ruditapes philippinarum. In. National Estuarine and Marine Exotic Species Information System (NEMESIS). [Accessed: 14 – 08-2023]. Available from: htps://invasions.si.edu/nemesis/species_summary/81477 Zeon, S.R., Koo, JH., Park, JW. et al. 2022. Estimation of Potential Habitats for Three Species of Bivalves Using the Habitat Variables in Gomso Bay Tidal Flat, Korea. Ocean Sci. J. 57, 607–617. htps://doi.org/10.1007/s12601-022-00085-9
Final Group Project Instructions Statistics for Social Research, Fall 2025 In the final project for this course, you will complete a data analysis project in a group of 2-3 students. This project will provide you with the opportunity to apply the methods and R skills you’ve developed over the course of the semester to analyze statistical relationships among variables in a dataset of your choice. Specifically, you will investigate the relationship between one outcome variable (Y) and one key predictor/explanatory variable (X). You will select a dataset to work with, identify a compelling research question that the data could help to answer, and answer the question using that data. The final group project report should be 2000-3000 words. Overview of Milestones and Deadlines 1. Oct 30, 2025 Sign up for group matching here (optional) 2. Nov 13, 2025 One-paragraph summary of project idea and names of group members due at 11:59pm 3. Dec 2, 2025 Drafts of 1) Introduction and 2) Data, sample, and key variables due at 11:59pm 4. Dec 13, 2025 Final report due at 11:59pm 5. Dec 13, 2025 Peer and self evaluation form. due at 11:59pm Selecting a Topic and Dataset As noted above, you will investigate the relationship between one outcome variable (Y) and one main predictor/explanatory variable (X). Your selection of focal variables (X and Y) must be logical and well-motivated. As such, you are expected to find and cite at least two academic articles to i) develop and motivate a research question about the relationship between these focal variables and ii) pose a testable hypothesis about what the relationship might look like. You may: 1. Use the Future of Families Dataset: for your convenience, I will upload a copy of the Future of Families Dataset to Brightspace. I will introduce this dataset in class. It contains a wide range of variables suitable for answering many sociological questions. 2. Choose your own adventure: you may also choose to locate your own dataset if you are interested in a specific topic. Here are some links to additional resources that you might find helpful: a. Pew Research: https://www.pewresearch.org/download-datasets/ (mostly opinion polls) b. 538: https://data.fivethirtyeight.com/ (sports, pop culture, politics). c. Data is Plural: https://www.data-is-plural.com/archive/ (assorted datasets on all sorts of topics) d. Directory of a lot of political science data: https://github.com/erikgahner/PolData Please note that within your chosen dataset, your outcome variable (Y) must be an interval or ratio variable (e.g., a crime rate, hourly wages, annual income, number of protest events attended, continuous test scores, etc.) There are no restrictions on the other variables you may select. General advice for choosing data sources (if not using Future of Families data) ● If you want to analyze the relationship between X and Y, make sure that these two variables are included in the data set. ● Ensure that the dataset has a sufficiently large sample size and that there are variables that you will actually be able to analyze with the skills you developed in this class. If you want to do more advanced data cleaning and/or merging, you’re welcome to do so, but it’s not required. ● Try to look for a ‘codebook’ or some other document that explains what the variables mean and how they are coded. Be especially careful with how different datasets record missing values. ● For some projects, preparing the data for analysis takes longer than the actual analysis itself. Try to find a dataset where you do not need to extensively recode / clean up the data before you run your analyses. This makes the final project easier. ● In a similar vein, if the data set is greater than about 50MB (this is not a hard cutoff), R commands and analyses tend to take longer. Loading alternate data formats You might encounter datasets that are saved in formats other than CSVs. R can load nearly all forms of data. If you run into a data file with the extension .dta, run the following sample code (make sure you’ve successfully set your working directory first though): install.packages(“haven”) # install if you don’t already have it library(haven) my_dataframe. New File -> R Markdown in RStudio. Please select the option to output to PDF. The final RMarkdown file should load the data you have selected, run any preprocessing that you need to conduct (i.e., clean your data for analysis if needed), produce any summary statistics or plots of your focal variables, and conduct the main regressions of interest for the project. The Rmd file and the resulting knitted PDF should both be uploaded to Brightspace. Only one submission is required per group. Outline of Project Components The following outline the key sections of your project. Please see me if you have any questions. Introduction -- 5 points 1) Provide a description of the phenomena to be studied (i.e., the focal relationship, what’s the outcome variable, what’s the key predictor) 2) Briefly explain why we should care about the relationship under consideration a) How does your project expand our knowledge of how the social/ political/economic world works? b) Identify any potential policy implications of this relationship 3) Preview your data and analytic techniques (two or three sentences maximum) a) What methods are you employing? Unless otherwise approved, everyone should be relying on ordinary least squares regression (i.e., linear regression) 4) Briefly highlight the central findings of your research. Please note that this component does not need to be included in the draft you submit on December 2nd. Literature review, research question(s), and hypothesis -- 10 points 1) What does the existing literature/research lead us to believe about whether, why, and/or how X and Y are related? Please cite at least two academic sources. 2) Are there any alternative explanations that might explain why X and Y are associated? That is, what other statistical control variables will you need to include in your regression model if you are interested in how X impacts Y? 3) Given your brief review of the literature, clearly state your central research question(s). 4) Drawing on existing literature and/or your own ideas, state and justify one or more hypotheses about what you expect to see in your data analysis. Please make sure that your hypotheses are 1) directly related to your research question and 2) can be addressed with the data you have. Data, sample, and key variables -- 10 points 1) Briefly discuss the data that you will be analyzing in the subsequent sections a) What is the unit of analysis? b) How, when, and where was the data collected? You may have to briefly review the dataset’s codebook. 2) How many observations are in your sample? If you’ve restricted the sample in some way, please indicate what you did and why. 3) What are the variables that you will be analyzing in the subsequent sections? a) What are their levels of measurement? What kind of variables are they? What are the units that they’re measured in (e.g., miles, points, percentage)? You may summarize this in a table if you wish. Descriptive statistics, plots, and interpretations -- 15 points 1) Calculate the appropriate descriptive/summary statistics for the focal variables used in your analysis (the outcome variable and key explanatory variable) a) Frequency and proportion tables for ordinal/nominal variables b) Mean, median, standard deviation, and range for interval/ratio variables 2) Report these in a professional-looking table (I will show you how to do this in R) 3) Produce a plot that summarizes the distribution of the outcome variable (e.g., a histogram) 4) Produce a scatterplot that illustrates the main relationship of interest. The outcome variable should be on the Y axis and the explanatory variable should be on the X axis. 5) Briefly interpret the tables and figures provided in this section in words. What do they tell you about the distribution of your key variables? Regression and interpretation -- 25 points 1) Estimate an ordinary least squares regression analysis of your focal relationship (i.e., a simple linear regression model, Y ~ X) a) Report the results in a professional table (I will show you how to do this in R) b) Provide an interpretation of the results presented in your regression table including the model fit (R^2) and the regression coefficients (and their statistical significance) c) Given your interpretation of results presented in the previous section, do you find evidence to support your research hypothesis? 2) What variable(s) do you need to control for to address confounding in the effect of X on Y? Provide a brief (1-2 sentence) reason for each control variable you think you should incorporate. 3) Estimate an ordinary least regression analysis of your focal relationship, but include the controls you reference above (i.e., a multiple regression model, Y ~ X + controls). a) Report the results in a professional table (I will show you how to do this in R) b) Provide an interpretation of the results presented in your regression table including the model fit (R^2) and the regression coefficients (and their statistical significance) c) Given your interpretation of results presented in the previous section, do you find evidence to support your research hypothesis? 4) Briefly explain why you believe your results changed or did not change between the simple linear regression and multiple regression models. Conclusion -- 15 points 1) Review the central purpose of your paper (to examine the relationship between X and Y) 2) Recap your central findings using clear and precise language. Be sure to connect your findings back to your primary research question. What overall answer do you arrive at? Evaluate the extent to which you find support for your hypothesis. 3) Critically assess the relationship that you examined by addressing each of the following points: a) Evaluate whether your analysis can be interpreted as revealing a causal relationship. Discuss what additional forms of unobserved confounding might remain. b) Identify at least one limitation of your research (all research has limitations!). You may consider any number of issues we’ve discussed in class, such as sampling, non-response, measurement, internal validity, and external validity. c) Identify at least one way your analysis could be improved (e.g., what better data could be collected, what other research designs could better get at the question)
Term Project AD 717 Final Project For your term project, you are going to build a portfolio of six stocks and write a prospectus of your mini-fund. Consider the following three investors: • Kim is a 25-year-old young professional, employed in a major city in the northeast. Since joining the workforce three years ago, they contribute as much money as possible to their retirement accounts which is invested in a diverse set of index funds. An avid fan of Benjamin Graham's "The Intelligent Investor", they have decided to consider a few individual stocks of companies with good and stable long-term prospects as well as a great management. • Nicole is 52 years old, and a few months ago, she retired from her well-paying job after aggressively saving and investing her money prudently for much of her life. While she could go back to work if necessary, she prefers her financial independence. In order to maintain a steady cash-flow, her portfolio is heavily geared towards high yielding stocks, allowing her and her family to live of dividend payments for the most part. Aware of the downturn of General Electric and their dividend cut, she focuses on companies from which she expects a solid and steady dividend growth. • Peter is in his mid 30s. He did not start a well-paying job until two years ago, and therefore, he is behind on his retirement savings. To make up for lost time, he is contributing the maximum allowed to his individual retirement account (IRA), which is invested in market ETFs. Additionally, he sets aside money every year for risky high-growth investments or appropriate short-selling opportunities. Select one of these investors as your client for whom you create the portfolio of six stocks. Your stocks must be in the stock price file on Blackboard. Stocks in that file are companies in the S&P 400 as of early January 2025 with five years’ worth of data. Then, perform. the following exercises: 1. Write two paragraph per stock in your portfolio explaining clearly (i) why this stock is a good choice for your portfolio given the investor profile and (ii) the company’s background. Support your answers with both description of the firm and their business model and appropriate financial ratios. 2. Copy your stocks’ prices from the shared spreadsheet on Blackboard. Compute monthly returns. (Note that you need 61 prices to compute 60 months’ worth of returns). 3. Download the file https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp/F-F_Research_Data_Factors_CSV.zip. In this file, you find excess market return, SMB, HML and the risk-free rate. Use the risk-free rate to compute the excess returns for your stocks. 4. Run a regression of the stocks’ excess returns against the excess market return to find the CAPM beta for each company’s shares. 5. Make a forecast for the alpha of each stock, that is, the return that you expect the stock to perform. minus the return predicted by the CAPM. Justify your alpha based on the firm’s business model and financial ratios. 6. Build an active portfolio with the six stocks according to Chapter 27.1 in our textbook. 7. Run a regression of the stocks’ returns against the excess market return, SMB and HML to find the market beta, SMB beta and HML beta. Categorize each company into a. defensive, neutral or aggressive for the market beta; b. small, neutral or big for the SMB beta; c. value, neutral or growth for the HML beta. 8. Run a regression on the portfolio with the weights you find in part 6 against the excess market return, SMB and HML to find the market beta, SMB beta and HML beta of the entire portfolio. 9. Based on your findings and the investment strategy, identify a benchmark portfolio against which you will compare your portfolio. Adjust the benchmark ETF or mutual fund for its riskiness. 10. Consider the mutual fund report above. Recreate the sections in purple for your portfolio. A bigger version of the image can be found at the end of this document. Notes on Fama-French Factors: • The Fama-French regressions give you a coefficient for the market risk of a stock or portfolio (βMKT), its exposure to the risk proxied by the size factor (βSMB) and its exposure to the risk proxied by the value factor (βHML). • The interpretation of βMKT is the same as before: o If an asset’s estimate for βMKT is 1, then it has the same market risk as the market portfolio. § Note that our regression estimate is simply that: an estimate that comes with uncertainty. An estimated βMKT of 0.95 or 1.05 is likely still consistent with a portfolio that has the same risk as the market portfolio. o If an asset’s estimate for βMKT is less (greater) than 1, then it is a defensive (aggressive) investment with respect to market risk. • The interpretation of βSMB is as follows: o If an asset’s estimate for βSMB is greater than 0, i.e., positive, then it behaves more like a portfolio that is long small companies and short big companies. o If an asset’s estimate for βSMB is less than 0, i.e., negative, then it behaves more like a portfolio that is short small companies and long big companies. o If an asset’s estimate for βSMB is indistinguishable from 0 because it’s p-value is greater than 0.05, then the assets is balanced with respect to firm size as measured by market cap. • The interpretation of βHML is as follows: o If an asset’s estimate for βHML is greater than 0, i.e., positive, then it behaves more like a portfolio that is long value firms and short growth firms. o If an asset’s estimate for βHML is less than 0, i.e., negative, then it behaves more like a portfolio that is short value firms and long growth firms. o If an asset’s estimate for βHML is indistinguishable from 0 because it’s p-value is greater than 0.05, then the assets is balanced with respect to value vs. growth. • Examples using 5 years of monthly data from 2018 to 2022: o VTV ETF, capturing large value firms in the US market: Coefficient Std. Error p-value MKT 0.876 0.025 0.000 SMB -0.133 0.051 0.012 HML 0.363 0.031 0.000 § The estimate for βMKT is 0.876, which is slightly below 1. We may classify this ETF as neutral to moderately defensive. § The estimate for βSMB is -0.133, which is negative with a p-value of 0.012, i.e., less than 0.05. We classify this ETF as behaving more like a portfolio short small firms and long big firms. We may also say the portfolio tilts slightly towards big firms since the coefficient is small in magnitude. § The estimate for βHML is 0.363, which is positive with a p-value of practically 0.000, i.e., less than 0.05. We classify this ETF as behaving more like a portfolio long value firms and short growth firms. We may also say the portfolio tilts towards value stocks since the coefficient is moderately big in magnitude. o XLV ETF, capturing the Health Care sector in the S&P 500: Coefficient Std. Error p-value MKT 0.715 0.065 0.000 SMB -0.221 0.132 0.100 HML -0.075 0.079 0.342 § The estimate for βMKT is 0.715, which is below 1. We may classify this ETF as moderately defensive § The estimate for βSMB is -0.221, which is negative with a p-value of 0.100, i.e., not less than 0.05. We classify this ETF as behaving like a portfolio that is neither overweight in small or big firms – or as neutral in the size factor. § The estimate for βHML is -0.075, which is negative with a p-value of practically 0.079, i.e., not less than 0.05. We classify this ETF as behaving more like a portfolio that is neither overweigh in value firms nor growth firms – or as neutral in the value factor.
PHIL 110 EXAM 2 – Extra credit All questions are worth 5 points. Partial credit will be given. 1. Explain the limitations of sentence logic. 2. Give an interpretation of Mxx & Fab. 3. Consider the following sentence and interpretation: a) Give all of the sentence’s substitution instances in this interpretation. b) For each substitution instance say whether the instance is true or false in this interpretation. c) Say whether the sentence itself is true or false in this interpretation. 4. Transcribe the following sentence into predicate logic twice. First use subscripted quantifiers, then unrestricted quantifiers. Use the following transcription guide: j: Jim, a: Angela, Px: x is a person, Pxy: x pranks y, Lxy: x loves y. “Angela loves everyone whom Jim pranks.” 5. Write a substitution instance of the following sentence using the name ‘a’: 6. Write an existential generalization of the following sentence: 7. Provide an interpretation that is a counterexample to the following argument: 8. Prove that the following argument is valid. You can use any rules of inference. 9. Prove that the following argument is valid. You can use any rules of inference. 10. Use argument by cases to prove that the following argument is valid. You can use any other rules of inference.
LM Economics of Financial Markets and Institutions Project Report 1 Introduction ● Your report should show the optimal allocation of assets (risk-free and risky assets) based on the optimizations. ● Choose five companies of your choice, making up your portfolio. ● This is an individual project so I expect that you work independently. Please do not choose the same portfolios or report very similar comments; any cooperative work will be penalised. ● You must upload TWO files on Canvas: 1. Your report in Word or PDF format. 2. The Stata do file so that I can replicate your results. ● The report should not exceed 750 words; tables and graphs are not included in the word count. Please include the word count at the top of your document. A penalty of 5 ● The report counts for 25% of the final mark. ● The deadline for submitting the project is clearly indicated on Canvas and on the remit. 2 Report Organization ● You should analyze your data using Stata. During Week 6, which is the assessment support week, the lecture will focus on preparing for the project. A ”do file” containing necessary commands, along with a recording of the Week 6 lecture that explains how to execute these commands, will be available on Canvas in the ’Project’ section. ● The report that you submit should be organized as a literate response to the questions, divided in paragraphs that can be understood by someone who didn’t just read the questions. ● Include your basic numerical results and graphs in your paragraphs along with the ap- propriate analysis and interpretation of them. ● Providing solely the calculations is NOT acceptable. A discussion of your findings, comparisons of the results, possible explanations for any differences found, and finally your recommendations for an investor wanting to hold this portfolio are essential. ● Please edit tables and graphs from Stata before inserting them in the document. ● Tables and graphs should be numbered, have a meaningful title, and an explanatory note at the bottom. ● The significance level of the coefficients must be indicated with an asterisk next to the coefficient, according to the significance level: * 10%, ** 5%, *** 1%. 3 Points to Discuss in the Report 1. Download monthly prices, from January 2014 through December 2023, on the market as a whole and on five individual stocks (for different industries) of your choice from Yahoo Finance. Briefly describe the stocks that you have selected. 2. Graph the time series of the prices. 3. Compute the returns using the closing prices: 4. Compute descriptive statistics (mean, standard deviation, maximum, and minimum) of the returns and report them in a table. 5. Look at the correlation and report the results in a table with the significance levels. 6. Get the frequency histograms of your returns. 7. Estimate and plot the linear relationship between each of your assets’ returns and the market returns. 8. Estimate the CAPM (reporting the results in a table): The annual risk-free rate is 2.4%. 9. Compute the following portfolios and report them in a table (one portfolio per column) indicating the weights, the expected return of the portfolio, the standard deviation of the portfolio, and the Sharpe ratio: ● The Global Minimum Variance Portfolio (GMVP), i.e., the portfolio that lies to the far left of the efficient frontier and is made up of a portfolio of risky assets that produces the minimum risk for an investor. ● Compute four portfolios: three choosing appropriate increments of the required re- turn above the GMVP and one with the maximum return. ● The optimal risky portfolio, i.e., the one at tangency between the efficient frontier and the capital market line. 10. Plot the efficient frontier on a return-risk diagram for a long-only constraint, not for long-short (where short selling is permitted). 11. Plot the optimal risky portfolio tangent to the capital market line. Do so for both a long-only constraint .
Problem Set 6 AEM 4110/5111 – Introduction to Econometrics Fall 2025 Note: Part II (seasonality) is optional Instructions • This problem set is due by 12/10 at 11:59pm. • Submit your answers via Canvas in the assignments section of the course. • Submit a zipped folder with the following documents. The zipped folder should be named according to “PS6” “lastname” 1. A write-up in PDF format with your answers to the questions below and the full names of all your group members. 2. A do-file with the Stata code you use for your answers. In the do-file, comment your script specifying which sections correspond to each answer in your write-up. 3. For the questions that require filling a table, you can create one in Excel or using LaTeX. 4. Important! Please write each answer on a separate page and clearly label it with the corresponding question number (for example, Question I.1.a, Question I.1.b, etc.). Set Up The Goal In this problem set, you will apply time series methods to analyze U.S. Consumer Price Index (CPI) data. Specifically, you will work with month-over-month CPI growth rates from January 1980 to March 2024. The dataset has been deseasonalized to focus on the core autoregressive and moving average structure; you will examine the original seasonal patterns in Part 2. Data: The file cpi data.dta contains the following variables: • cpi deseason: Deseasonalized month-over-month CPI growth rate (in percentage points) • cpi raw: Original (non-deseasonalized) month-over-month CPI growth rate • date: Date variable (monthly, from 1980m1 to 2024m3) • t: Time index (1, 2, 3, ..., 531) The cpi raw series comes from the Federal Reserve Bank of St. Louis website FRED. Part I: Model Selection In this part, you will work exclusively with the deseasonalized CPI growth series (cpi deseason). 1 Let’s start with some data exploration a) Load the dataset and declare it as time series data using the tsset command. b) Create a time series plot of cpi deseason using the tsline command. Include this graph in your submission. c) Briefly describe the visual properties of the series. Does it appear to fluctuate around a constant mean? Are there any obvious trends or structural breaks? 2 Next, we want to make sure that the series is stationary. a) Conduct an Augmented Dickey-Fuller (ADF) test for cpi deseason using the dfuller com- mand as we saw in class. b) Report the test statistic, and the 1%, 5%, and 10% critical values. c) State the null and alternative hypotheses for the ADF test. Based on your results, do you reject or fail to reject the null hypothesis at the 5% significance level? d) Interpret your conclusion in plain language: is the series stationary or non-stationary? Why do we want a stationary series? 3 Let’s now use the ACF and PACF to help us guide the choice of the model. a) Generate and display the autocorrelation function (ACF) for the first 24 lags using the ac command. Include the graph in your submission. b) Examine the ACF plot. Which lags have autocorrelations that are statistically significant (i.e., outside the confidence bands)? Describe the overall pattern (e.g., does it decay gradually or cut off sharply?). c) Generate and display the partial autocorrelation function (PACF) for the first 24 lags using the pac command. Include the graph in your submission. d) Examine the PACF plot. Which lags have partial autocorrelations that are statistically significant? Describe the pattern. 4 We are now going to use the command arima to estimate different ARMA models, and use the Information Criteria to help us select the model among them that best fits the data. Estimate the following six ARMA specifications for cpi deseason: i) AR(1): arima cpi deseason, ar(1) ii) AR(2): arima cpi deseason, ar(1/2) iii) MA(1): arima cpi deseason, ma(1) iv) MA(2): arima cpi deseason, ma(1/2) v) ARMA(1,1): arima cpi deseason, ar(1) ma(1) vi) ARMA(2,2): arima cpi deseason, ar(1/2) ma(1/2) For each model: a) Report the estimated coefficients for the AR and MA terms, along with their standard errors and p-values in a table for each model. b) Briefly comment on the signs of the significant coefficients. Do they align with the patterns you observed in the ACF and PACF? c) After each regression, use the estat ic post-estimation command to obtain the Akaike In- formation Criterion (AIC) and Bayesian Information Criterion (BIC) for each model. d) After compiling the table for all 6 models: Which model is selected as “best” according to AIC? Which model is selected as “best” according to BIC? Do the two criteria agree? Note: • Run estat ic immediately after each arima estimation to capture the AIC and BIC values before proceeding to the next model. • For part c), compile the AIC and BIC values for all six models into one comprehensive comparison table to facilitate model selection. 5 In class we discussed that the residual of a “good model” should not contain any information that helps us predict future values of the series. In other words, we want our residuals to be “White Noise”. Let’s verify that this is the case for the model you selected in Question 4 (use the BIC criterion if AIC and BIC disagree). For this model: a) After estimation, predict the residuals using predict resid, residuals. b) Plot the residuals to see their distribution. Use the command histogram resid, bins(40). Do the residuals appear approximately normally distributed? Is the distribution centered around 0? c) [For AEM 5111 only] Generate the ACF and PACF of the residuals for the first 20 lags using ac resid, lags(20). Include the graph in your submission. d) [For AEM 5111 only] Based on the ACF and PACF of the residuals, do you think that the residuals are ~ i.i.d. N(0,σ2 )? Why/why not? What does this suggest about model adequacy? Optional Part II: Seasonality In Part I, you worked with deseasonalized data to focus on the core ARMA structure. In this part, you will examine the original, non-deseasonalized CPI growth series (cpi raw) to understand why deseasonalization was necessary and how it can be performed. 1 Let’s start with some visual exploration of the series cpi raw. a) Create a time series plot of cpi raw using tsline. Compare this visually to the plot of cpi deseason from Question 1 in Part I. Do you notice any recurring patterns or cycles in the raw series? b) Generate the ACF for cpi raw with 24 lags. Include the graph in your submission. c) Generate the PACF for cpi raw with 24 lags. Include the graph in your submission. d) Looking at the ACF for cpi raw, at which lag(s) do you see particularly large spikes that were not present (or much smaller) in the deseasonalized data? What does this tell you about the seasonality of the data? 2 [AEM 5111 only] Let’s now see how we can deseasonalize the data. The most simple way to remove seasonality is to include month-of-year dummy variables in a regression and retain the residuals. This method explicitly estimates and removes the average “effect” of each calendar month. The residuals contain the variation in the series which is not explained by the monthly patterns. a) First, create a month variable: gen month = month(dofm(date)) This extracts the month (1=January, 2=February, . . . , 12=December) from the date. b) Run the following regression: reg cpi_raw i . month This is equivalent to regressing cpi raw on 11 dummy variables and a constant. c) Explain what each coefficient in this regression represents. For example, what does the coefficient on 2 .month (February) tell you? d) Generate the residuals from this regression: predict cpi_des , residuals These residuals represent the deseasonalized series: they are what remains of cpi raw after removing the average effect of each month. e) Plot the ACF and PACF of the cpi des variable. What do you notice? How does it compare to the graphs you obtained from the raw series? Optional Questions a) Why would it be a problem to estimate the ARMA model on the raw series, i.e., without accounting for seasonality? b) In the previous question, we removed the predictable effect of each month on the cpi raw variable. Imagine instead that you are interested in removing the effect of each quarter of the year. How would you do it? Please describe how you would modify the above procedure. Notes on Deasonalization Method The series cpi deseasonalized was obtained using a dif- ferent deseasonalization procedure called “ X-13ARIMA-SEATS”. This is a method developed by the U.S. Census Bureau and used by professionals. You can read more about it here. Using dummies to deseasonalize the series is very simple, but a drawback is that it imposes that the effect of each month is constant over the years.
Title: Individual Assignment Course: Monetary Economics and Macroeconomy Question 1 Simple Taylor Rule Estimation 1. Download the data set EstimTaylorRule_Data_AA .csv (available on Canvas) for country AA of your choice (UK: United Kingdom, US: United States). Use it to perform a simple OLS estimation of the Taylor rule it = φy gy,t + φπ πt + εt , where it is the (policy) interest rate, gy,t is real GDP growth, and πt is in ation. (a) Report the estimated values for the coe cients φy and φπ . Does φπ satisfy the Taylor principle? (b) Draw a graph plotting the estimated Taylor rule (ˆ(1)t ) against the actual interest rate. The data set contains two time series for real GDP growth (percentage change from a year earlier, and percentage change from the previous quarter at an annual rate) and two time series for in ation (headline in ation, and core in ation, which excludes food and energy). You may use whichever pair you prefer. 2. Describe two problems or disadvantages of this approach to estimating a Taylor Rule. (Hint: Think about (i) structural breaks, (ii) endogeneity). Question 2 Simple New Keynesian Model Consider the baseline New Keynesian model. The model can be described by the following equations: The rst equation is the IS curve, the second is the Phillips curve, and the third is the monetary policy rule. We have where ω is the fraction of rms that cannot change prices. β ∈ (0, 1) is the discount factor, σ > 0 is the inverse of the intertemporal elasticity of substitution, and ϕπ > 1 measures how strongly monetary policy reacts to in ation. Equations (IS), (PC), and (MP) determine the dynamic paths of the endogenous variables {xt ,πt , it } , given the exogenous shocks {vt , ut }. 1. Brie y describe the economic intuition behind the three equations. 2. Combine (MP) with (IS) and (PC) to eliminate it from the system and rewrite the remaining two equations in matrix form as where A is a 2 × 2 matrix and B is a 2 × 1 vector. What are A and B? 3. Show that the assumption ϕπ > 1 is crucial to ensure uniqueness of the equilibrium. Hint: you have to show that both roots of the characteristic equation λ2 −tr (A) λ+ det(A) = 0 are larger than one in absolute value, where tr(A) denotes the trace of the matrix A and det(A) is the determinant. Discuss the economic intuition. 4. Assume that the monetary policy shock ut follows a stationary autoregressive pro- cess ut = ρuut-1 + εt , with − 1 < ρu < 1 where εt is an i.i.d. normal innovation with mean zero. For simplicity, set the shock to the IS curve equal to zero, i.e. vt = 0 for all t. Solve for the equilibrium paths of xt and πt using the method of undetermined coe cients. In particular, conjecture that in equilibrium xt = ψxu ut and πt = ψπuut Substitute these conjectures into the IS-PC-MP equations and solve for the unde- termined coe cients ψxu ,ψπu. 5. Let us analyze the economy's response to an increase in ut (i.e. a contractionary monetary policy shock). (a) Show analytically that ψxu < 0, ψπu < 0 for all admissible parameter values. What is the economic intuition? (b) Derive analytically the equilibrium paths for the nominal interest rate it and for the real interest rate rt = it - Et πt+1 . A friend of yours claims: Clearly, a positive shock to ut will induce an increase in both the real and the nominal interest rate. Is this statement true or false? Explain. 6. Now use the computer (Matlab or Excel) to simulate the response of the economy to a unit increase in ut. Speci cally, in period t = 1 we have u1 = 1, then u2 = ρu , u3 = ρu(2), and so on. Assume the following parameter values: β = 0.99, ϕπ = 1.5, σ = 1, ω = 0.8 and ρu = 0.5. Show the impulse responses of {xt ,πt , it , rt } in a single chart. How would your ndings change if ω = 0.4? Discuss the economic intuition. (Hint: recall that ω is the fraction of rms that cannot change prices).
Guidelines for Calculus Application Project This project requires students to choose a problem that can be solved using fundamental concepts of calculus and write an essay (approximately 10 pages). The purpose is to demonstrate the ability to transform. real-world or theoretical problems into mathematical models, analyze them using calculus methods, and interpret the results meaningfully. Students may refer to the following general writing structure and directions. Suggested Structure 1. Title: Concise and clearly reflects the core problem studied. 2. Abstract: Briefly describe the objective, methods, and main conclusions. 3. Introduction: Introduce the background, significance, and related studies. 4. Model Formulation: Present assumptions and construct a mathematical model based on the problem. 5. Solution: Use calculus tools (derivatives, integrals, differential equations, etc.). 6. Results and Discussion: Interpret the results, explain their practical meaning, and discuss limitations. 7. References: List all consulted papers, or other resources in an academic format. Possible Topics • Optimization and extremum problems of functions. • Calculation of area, volume, or work. • Motion and velocity-acceleration relationships. • Applications in economics: cost, revenue, or optimal pricing models. Writing Tips • Keep logic clear and derivations complete. • Use figures and equations appropriately to clarify ideas. • Cite all references accurately and consistently.
ENG1001 University English (I) Course Assessment – Essay Writing (50%) Instructions Write a 500-word essay (±10%) discussing the environmental impacts of artificial intelligence (AI). Your essay must include an introduction, body, and conclusion. The introduction should provide background information, state the purpose of your essay, and include a clear thesis statement. The body should demonstrate your ability to construct coherent paragraphs, each with a topic sentence and supporting details. You must incorporate evidence from the following articles to support your ideas · Article 1: What opportunities and risks does AI present for climate action? https://www.lse.ac.uk/granthaminstitute/explainers/what-opportunities-and-risks-does-ai-present-for-climate-action/ · Article 2: Explained: Generative AI’s environmental impact https://news.mit.edu/2025/explained-generative-ai-environmental-impact-0117 In the conclusion, summarise the main points and restate your thesis in a way that reinforces your ideas. Your essay should be well-formatted and proofread. Assessment Criteria Your essay will be assessed on content, organisation, and language, with each criterion weighing 10%. Academic Integrity Plagiarism is strictly prohibited and will result in severe penalties, including potential failure of the module. You must cite the two assigned articles using APA style, including in-text citations and a reference page. Refer to the assignment template for guidance. This assignment is designed to assess your original thinking and writing skills. Your essay must be original, and the writing style. must be consistent with your in-class writing. Excessive reliance on AI tools, such as submitting an essay primarily generated by AI without substantial original contribution, will lead to mark deductions or failure of the assessment. Please refer to the assignment rubrics for further details. If you use AI tools (e.g., ChatGPT) to generate ideas or content, you must: · Clearly cite the AI tool as a source, following APA guidelines (see https://apastyle.apa.org/blog/how-to-cite-chatgpt). · Keep a detailed record of all interactions with AI tools, as you may be required to submit this record with your essay. · Failure to properly attribute AI-generated content may be considered academic dishonesty and could lead to mark deductions or failure of the module. Submission Details · Deadline: Submit by the end of Week 15 via Moodle. · Format: Use A4 sheets, double-spaced, Times New Roman, font size 12. Please refer to the essay template for further details. · AI Detector Report: Attach screenshot(s) of an AI detector report from one of the recommended tools (Copyleaks, Scribbr, or Originality.ai) on the last page of your submission. Failure to include the report will result in a mark deduction. · Word Limit: 500 words (±10%). Marks will be deducted for submissions outside this range. · Backup: Keep a copy of your assignment. · Late Submission: A 10% deduction per school day will be applied to late submissions. Assignments submitted five school days late will receive no marks.
Old Final Exam – Econ 0200 1. For the following game: A B A 1,1 15,4 B 4,15 7,7 a) (2 points) Which outcomes are Pareto optimal? b) (4 points) List all NE in pure strategies c) (1 point) If this fits the definition of one of our seven named games, name it. Otherwise, write “none”. d) (2 points) When testing whether or not A is ESS, what is A’s fitness and B’s fitness? e) (1 point) Is A ESS? f) (2 points) When testing whether or not B is ESS, what is A’s fitness and B’s fitness? g) (1 point) Is B ESS? h) (4 points) What is the static midpoint in an evolutionary setting? Write “none” if none exists. i) (1 point) If a static midpoint exists, is it stable? If none exists write “none”. j) (1 point) List all dominant strategies for this game. If no strategy is dominant, write “none”. k) (4 points) draw the evolutionary graph for this game l) (4 points) draw the best response graph for this game 2. For the following game: A B A 12,12 5,12 B 12,5 16,16 a) (2 points) Which outcomes are Pareto optimal? b) (4 points) List all NE in pure strategies c) (1 point) If this fits the definition of one of our seven named games, name it. Otherwise, write “none”. d) (2 points) When testing whether or not A is ESS, what is A’s fitness and B’s fitness? e) (1 point) Is A ESS? f) (2 points) When testing whether or not B is ESS, what is A’s fitness and B’s fitness? g) (1 point) Is B ESS? h) (4 points) What is the static midpoint in an evolutionary setting? Write “none” if none exists. i) (1 point) If a static midpoint exists, is it stable? If none exists write “none”. j) (1 point) List all dominant strategies for this game. If no strategy is dominant, write “none”. k) (4 points) draw the evolutionary graph for this game l) (4 points) draw the best response graph for this game 3. What is the present value of each of the following future payments? a) (1 point) $1,000,000 received in 9 years if the interest rate is 7%? b) (1 point) $100,000 received in 5 years if the interest rate is 6%? c) (1 point) $200,000 received in 12 years if the interest rate is 2%? d) (1 point) $500,000 received in 40 years if the interest rate is 11%? e) (1 point) $1,000,000 received in 7 years if the interest rate is 60%? 4. For the following game: A B A 7,7 26,6 B 6,26 19,19 a) (2 points) Which outcomes are Pareto optimal? b) (4 points) List all NE in pure strategies c) (1 point) If this fits the definition of one of our seven named games, name it. Otherwise, write “none”. d) (4 points) When starting from a population mix of 50-50, what is the population mix 1 generation later? e) (1 point) Is A ESS? f) (1 point) Is B ESS? g) (2 points) In an infinitely repeated setting, what interest rate condition would be required to sustain cooperation if both players were to play grim trigger? h) (2 points) In an infinitely repeated setting, what interest rate condition would be required to sustain cooperation if both players were to play tit-for-tat? i) (2 points) In an indefinitely repeated game, if the probability of playing subsequent rounds is 40% after each round concludes, which strategies sustain cooperation – Grim Trigger, Tit-for-tat, both, or neither? j) (4 points) draw the evolutionary graph for this game k) (4 points) draw the best response graph for this game 5. For the following game: A B A 200,200 12,210 B 210,12 50,50 a) (2 points) In an infinitely repeated setting, what interest rate condition would be required to sustain cooperation if both players were to play grim trigger? b) (2 points) In an infinitely repeated setting, what interest rate condition would be required to sustain cooperation if both players were to play tit-for-tat? c) (2 points) In an indefinitely repeated game, if the probability of playing subsequent rounds is 7% after each round concludes, which strategies sustain cooperation – Grim Trigger, Tit-for-tat, both, or neither? 6. Suppose a very large number of players are trying to guess a target number T, where the target is equal to 3/4 of the average plus 10. Players can pick any number from -100 to 100. a) (2 points) What is the Nash Equilibrium? (All players guess what number?) b) (3 points) What are level 1 through level 3 rationalizable ranges?Old Final Exam – Econ 0200 7. For the following game: L R U 9,4 13,3 D 4,6 13,7 a) (2 points) Which outcomes are Pareto optimal? b) (4 points) List all NE in pure strategies c) (1 point) If this fits the definition of one of our seven named games, name it. Otherwise, write “none”. d) (4 points) What is the mixed strategy equilibrium? If none, write “none”. If more than one, write “many”. e) (4 points) draw the best response graph for this game 8. For the following game: L R U 12,7 3,1 D 2,2 9,13 a) (2 points) Which outcomes are Pareto optimal? b) (4 points) List all NE in pure strategies c) (1 point) If this fits the definition of one of our seven named games, name it. Otherwise, write “none”. d) (4 points) What is the mixed strategy equilibrium? If none, write “none”. If more than one, write “many”. e) (4 points) draw the best response graph for this game 9. For the following game: a) (4 points) List all NE in pure strategies b) (4 points) List all SPNE in pure strategies 10. For the following game: a) (4 points) List all NE in pure strategies b) (4 points) List all SPNE in pure strategies c) (2 points) List all Pareto optimal outcomes 11. Suppose we have 2 firms in an industry. Demand is represented by the following equation: P = 750 – Qt and costs for firm 1 are 238/unit + 10,000 fixed cost, while costs for firm 2 are 174/unit + 20,000 fixed cost. a) (3 points) What is the NE in the pure Bertrand model? State price, quantity and profit for each. b) (4 points) What is each firm’s best response function under Cournot? c) (3 points) What is each firm’s equilibrium quantity, price and profit under Cournot? d) (3 points) What are the level 1 through level 3 rationalizable strategies for each firm under Cournot? 12. Suppose we have 3 identical firms in an industry. Demand is represented by the following equation: P = 125 – (1/100) Qt and each firm’s cost = 29 per unit + 20,000 fixed cost. a) (1 point) What is the NE in the pure Bertrand model? State the price that each firm charges. b) (2 points) What is firm 1’s best response function under Cournot? c) (3 points) What is firm 1’s equilibrium quantity, price and profit under Cournot? d) (1 point) If there were only 2 firms in the Cournot model, what is firm 1’s quantity? e) (1 points) If there were only 1 firm in the BERTRAND model, what is that firm’s price? f) (2 points) EXTRA CREDIT: What is the largest number of firms that can profitably coexist in this industry under the Cournot model? g) (2 points) EXTRA CREDIT: What is the largest number of firms that can profitably coexist in this industry if the firms collude? 13. Suppose there are 400 voters, and 5 candidates: Steve Jobs, Bill Gates, Elon Musk, Jeff Bezos and Mark Zuckerberg, 87 voters prefer: Zuckerberg > Gates > Jobs > Bezos > Musk 30 voters prefer: Gates > Zuckerberg > Jobs > Bezos > Musk 73 voters prefer: Bezos > Zuckerberg > Gates > Jobs > Musk 129 voters prefer: Musk > Jobs > Gates > Bezos > Zuckerberg 16 voters prefer: Gates > Bezos > Jobs > Zuckerberg > Musk 65 voters prefer: Jobs > Bezos > Gates > Zuckerberg > Musk For each candidate, please fill in their votes – if a candidate is not involved in the relevant round, please leave it blank (so for part b, you may only have vote totals for 2 candidates and 3 should be blank). (3 points each) a) Who wins a plurality vote, and what are the vote totals? b) If you follow the instant runoff method (if no one reaches 50%, the top two from the plurality vote have a runoff), who wins, and what is the vote total for each? c) With ranked-choice voting, eliminating the lowest and redistributing, who wins and what is the vote in the round that they win? d) For a Borda count method, who wins and what are each candidates totals? (use 4/3/2/1/0 points for first/second/third/fourth/fifth) e) Who is the Condorcet tournament winner, if any? If there is no winner, say “none”. What is a possible vote total in the final tournament round? f) If using Donald Saari’s preferred method: Borda count, top two go head-to-head in a run-off, who wins and what is the vote total in that runoff election? g) If the addition of a sixth candidate, Richard Branson, changes the Borda count relative ranking of Musk vs. Bezos, which axiom of Arrow’s Impossibility Theorem is violated? 14. (4 points) EXTRA CREDIT: Write down a non-trivial 2x2 normal form. game where the best response graph is two overlapping solid squares.
ASSESSMENT TASK 3 (GROUP): APPLYING FAMILY BUSINESS THEORY TO REAL-WORLD CHALLENGES REPORT Assessment Task: Video production offers a powerful medium for students to demonstrate their understanding of complex concepts in family business. In this assignment, each group will select one family business theory and apply it to address a real or hypothetical problem within a family business setting. The group will produce a 3 to 5-minute video that explains the theory and illustrates how it guides decisionmaking and problem-solving in the chosen context. In addition to the video, students are required to submit a written report that documents their analytical process, team reflections, and evaluation of outcomes. This project encourages collaborative learning, critical thinking, and the practical application of theory developing your problem-solving skills as defined in the learning outcome. Each group is required to: 1. Select one theory from the list of approved Family Business Theories (see below). 2. Formulate a problem, challenge, or situation in a family business context that can be analyzed through the chosen theory. 3. Develop a 3 to 5-minute video explaining the chosen theory and demonstrating how it can be used to address the problem. 4. Submit a written report (1,500-2,000 words) reflecting on the process and evaluating the outcome. It is designed to nurture your ability to reflect, analyze, and implement practical solutions to open-ended business issues commonly faced in family enterprises. List of Family Business Theories (Groups within the same tutorial session may not choose the same theory; selection is on a first-come-first-served basis.) 1. The Systems Theory 2. Agency Theory 3. Resource-Based View 4. Stewardship Theory 5. Socioemotional Wealth (SEW) Theory 6. The 12S Model Assessment Components Component Description Weightage Part A Video (3 to 5 min)+Presentation (10 min) 20% Part B A Written Report (1,500-2,000 words) reflecting on the process and evaluating the outcome. 20% Total 40% Assessment Weightage: 40% Total Word Count: 1,500-2,000 words (excluding title page, rubric, table of contents, references, appendices, and figures/tables) Assessment Requirements Part A: Video (3 to 5 min) + Presentation (10 min) (20%) Each group is required to submit a 3 to 5-minute video and deliver a 10-minute live presentation explaining their analytical process, team reflections, and evaluation of outcomes. These sessions are designed to support your development in applying family business theories, frameworks, and problem-solving strategies. Presentation Schedule Weeks 12 and 13 Exact date and time will be assigned based on your tutorial group schedule. You are expected to share your video and deliver a 10minute live presentation on the day of presentation. 1. Video Requirements Your group video must: • Clearly introduce the selected family business theory. • Present a real or hypothetical problem commonly faced by family businesses. • Apply the chosen theory to analyze, interpret, or solve the identified problem. • Reflect on the decision-making process, including ethical and cultural considerations. • Use engaging visuals, clear narration, and relevant, practical examples. The video should be edited for clarity and professionalism. Visual storytelling, diagrams, and animation are encouraged.
IOM205 Advanced Database Management 1st SEMESTER 2025/26 Group Coursework INSTRUCTIONS TO CANDIDATES 1. Your work must be submitted electronically through Learning Mall Online by 00:00 AM, OCT 20th 2025. 2. This coursework accounts for 30% of the final mark in this course. 3. This is a group coursework. a) Only the team leader needs to submit the files on LMO. b) Marks are awarded to the group as a whole; every member receives the identical score. 4. Generative AI is not allowed in completing this coursework. Coursework Title: Group coursework: Designing a Database Scenario Context UniBooks is a small start-up company specialising in second-hand textbooks. The company buys surplus academic books in bulk from publishers but also buys individual books from students. The books are advertised and sold via the company’s website. You have been approached to develop a database system for the company. The system needs to be able to store details of the books held in stock, to process incoming books and to record all sales. The system will also need to be able to perform other functions, such as producing invoices and different management reports. Specification UniBooks supplies textbooks to university students at discounted prices. The company obtains stocks of books directly from publishers and students: • Usually, UniBooks is able to purchase large stocks of books from publishers for 30% of the cover price. • After completing a course, a student may wish to sell his/her unwanted textbooks. UniBooks buystextbooks directly from students for 20% of the cover price. • All books are sold to the public for 80% of the cover price. There is also a standard charge of ¥10 for postage and packaging, regardless of the size of the orderplaced. The current system suffers from several limitations: • Occasionally, a customer will order a book that is not held in stock (e.g., print on demand titles). A staff member will need to search for details of the book’s publisher, and then contact the publisher to see ifUniBooks can obtain a copy of the book. The current system does not provide a search facility that can be used to locate a publisher’s details. • When stocks of a given book run out, it is left to a staff member to reorder a fresh supply from publishers. This raises two problems: customer orders are delayed until new stocks ofthe book arrive, and there is inconsistency regarding the number of books ordered from publishers. As an example, sometimes too few or too many books are ordered, resulting in further delays to customers or increased inventory costs. Ideally, it should be possible to set reorder levels and reorder quantities for booksto improve inventory control. • Management information takes a great deal of time to produce since it is collected and processed manually. As a result, managers are only able to see important information, such as sales figures, on a monthly basis. Ideally, management information should be available on demand. • Most publishers offer discounts based on order size (in addition to the discount over the cover price). In general, discounts are given as shown below in Table 1. At present, UniBooks often fails to claim the discounts it is entitled to. Table 1: Discount from publishers ofTotalOrderValue • UniBooks offers discounts to customers based on order size (in addition to the discount over cover price). In general, discounts are given as shown below in Table 2. Currently, these discounts are processed manually, and the sales information is not recorded accurately. Table 2: Discount to buyers ofTotalOrderValue Task Details and Description: The primary task for your group is to go through the scenario context and specification to understand and analyse the company’s data and information requirements. This should help you to design an appropriate database structure, which can meet the requirements of the organisation. In developing, realising and implementing the design, your group must create sample records (dummy data) for the identified entities. This is a group task and each member of the group must complete an equal share of the work. A list of tasks (not exhaustive) that you will need to perform. as a group in completing this coursework are given below. Tasks: 1. Decide upon the entities to create tables and corresponding attributes you will need, to address a range of requirements stemming from the scenario and specification. Example entities: customer, book, student, employee, order, etc. (Note: this is not an exhaustive list.) 2. Create an Entity-Relationship Model (ERM) using Microsoft Access to address the requirements. This model must be normalised to reduce data redundancy and improve data integrity. 3. Include sample records (at least four) in Microsoft Access for each table after developing the ERM and include validation of the attribute types, constraints and primary/foreign keys. 4. Reflect upon your ERM, discuss two issues/limitations associated with the design and anticipated operation of your database, and its impact on the business, i.e., how it might affect the business. Note: All these above the tasks will help you to make progress and completing this group coursework. Upon completion of the group coursework, the deliverables produced will provide a suitable starting point for the individual coursework. Deliverables: You MUST submit the following three separate files electronically to complete this coursework. Your team leader is responsible for submitting all required documents before the deadline. • Deliverable 1 (25%): The Group report (a MS word document) should not exceed 500 words. Marks of up to 5% points will be deducted if you exceed this word limit. Estimated word limits for each section are provided below to help you write the report. • Deliverable 2 (50%): Entity Relationship Model as a PDF document from Microsoft Access. • Deliverable 3 (25%): Your Microsoft Access Database File Contents of the report (Deliverable 1) • A separate cover page of the report must include your group number and student information (including name and ID) for each member in the group. [No word count applies] • Briefly explain the normalisation and resolving m:m relationship process with the aid of a suitable example (use the same example for each process step) drawn from your own ER model. [estimated word limit – not more than 300 words] Tip: You should not define normalisation and describe its objectives, rather explain how you have employed normalisation and resolved m:m relationship in your ER model (using at least one suitable example). • A brief discussion of two issues associated with the design and anticipated operation of your database, and how these issues may impact the business/organisation. You may discuss any issues/problems for which a solution is not yet clear, or where there are competing alternative designs. [Estimated word limit – not more than 200 words]. Tip: To score a passing mark for this component, you MUST at minimum discuss two issues suitably in your report (as stated above). Note: 1. Your work will be assessed on robustness, correctness, design meeting the business requirements, and the overall quality of your design. Please refer to the grading criteria at the end of this document, to know how each component or a combination of components will be graded. 2. Please ensure you have created one or more back-ups of your work in suitable places using appropriate mediums available to you, to avoid losing the work you may have already done. Learning Sessions Relevant to this Coursework Week 1: Introduction to Databases Week 2: Entity Relationship Modelling Week 3: Normalisation Week 4: Recap Week 5: Assignment workshop
Assignment 2 Digital Image Processing 1 Filtering in the Frequency Domain (40pts) a) (10pts) Apply the 2-D DFT to the image below using cv2.dft(), then visualize the Fourier power spectrum and the phase angle. The skeleton code is provided in assi-gnment2 1.py; you need to fill the missing parts (i.e., lines 19-22) and show the results in your report. (You may need to refer: https://opencv24-python-tutorials.readthedocs.io/en/latest/py_tutorials/py_imgproc/py_transforms/py_fourier_transform/py_fourier_transform.html) b) (10pts) Please explain what the phase angle and the power spectrum refer to (obtained in a)), and how frequency components are related to image contents. c) (20pts) Please use the skeleton code assignment2 1.py to finish the following tasks: • Filter out the high-frequency parts of image (include both spectrum and phase an-gle) obtained in a) using an ideal low-pass filter with a cutoff frequency 30. Then, transform. the new frequency map back into the spatial domain using cv2.idft(). (you need to fill in lines 48-58.) • Filter out the low-frequency parts of image (include both spectrum and phase an-gle) obtained in a) using an ideal high-pass filter with a cutoff frequency 30. Then, transform. the new frequency map back into the spatial domain using cv2.idft(). (you need to fill in lines 60-64.) In you report, you should show the two processed images in the spatial domain and explain their differences. Based on your observation, please explain whether ideal filters are good filters in practice? 2 Image Degradation and Restoration (30pts) a) (5pts) Use the pepper-salt noise to degrade the image below. (probability of salt noise: 0.25, probability of pepper noise: 0.25; the code is provided in assignment2 2.py, you need to fill in lines 22-30.) b) (10pts) In this part, we try to restore the image degraded by the pepper-salt noise obtained in a) using two different types of filters. • The arithmetic mean filter with a kernel size 7 × 7. (you need to fill in lines 46-56) • The median filter with a kernel size 7 × 7. (you need to fill in lines 60-69) In your report, it should contain two images restored by different filters. Besides, com-parisons between different restored images are required. (the skeleton code is provided in assignment2 2.py.) c) (15pts) Suppose we have a degradation system that can blur images using a low-pass gaussian filter (the gaussian low-pass filter is given in the gaussian low pass.npy). Please restore the corresponding degraded image below using the inverse filtering. In your report, you need to display results with different cutoff radius (i.e., 40 and 110), and explain the differences. (you need to fill in line 101, and change the cutoff radius in line 87; the skeleton code is provided in assignment2 2.py.) As shown below, you have three optional solutions to calculate Fˆ(u, v) and you can choose one of them. Note that you will get bonus points if you try more than one solution in your report. 3 Data Compression (30pts) a) (20pts) In our computer system, each character will occupy 1 bytes (8 bits). Given a string ’AAABBCCCCCCCDDDAAAAA’, please use the Huffman coding to compress it. 1) Construct the Huffman tree and determine the code for each symbol. For this question, you can hand-draw the tree construction process and take a photo to include in your document. (10pts) 2) Calculate the required bits before and after applying Huffman coding, and find the compression ratio. (10pts) b) (10pts) Please use the provided code assignment2 3.py to compress a 512 × 512 RGB image (’1.bmp’). You can try adjusting the quantization tables (lines 29-55) to obtain a compressed file (’1.gpj’) with different sizes. Then, you can decompress the compressed file to obtain the newly recovered image. Describe your adjustment process and your findings. Note: the source code should be attached with your submission.
