# 代做115.213 Quantitative Methods for Business代写留学生Matlab程序

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**115.213**

**Quantitative Methods for Business**

**Final Assessment**

**Total Marks: 100**

**1. INTRODUCTION**

In this assessment, you are required to follow the instructions / requirements given in Section 3 of this document while working with the data set provided on the Stream site (Data - Final Assessment - QM – 2024.xlsx). You should submit an excel file with the solution for each part of the assessment’s instructions / requirements. You can use the attached excel file (Answer Sheet - Final Assessment - QM – 2024.xlsx) to use as template for your submitted assessment. Please note that the formulae and steps carried out by you should be visible and accessible by the reader. In other words, do not copy the calculations / graphs and paste them as numbers in the excel file. Also, put the comments’/discussions’ part required in the instructions in clearly visible location in excel file (in other words, if you put the discussion part of the analysis in a cell that is too far in row or column, it might not be obvious that you provided the discussion part required in the instruction).

**2. DATA AND VARIABLES**

The data is provided in the Sheet named ‘Data’ in ‘Data - Final Assessment - QM – 2024.xlsx’ file uploaded in this section of Stream site. This data comes from a survey in the United States of America, showing individuals’ (respondents’) characteristics captured in different variables. The description of the variables is given in Sheet named ‘Variables’ in ‘Data - Final Assessment - QM – 2024.xlsx’ file.

**3. INSTRUCTIONS / REQUIREMENTS**

You are required to carry out different steps using the same data set. The instructions / requirements for each step, along with associated marks for each step, are given as follows:

1) Plot the Total Wealth variable and discuss its distribution. Also explain the steps that can be taken to improve the distribution of the Total Wealth. Marks: 6 Marks

2) Present suitable descriptive statistics for variables of your choice and explain the estimates in your own words. Marks: 8 Marks

3) Present suitable descriptive statistics for variables of your choice for different categories of Female variable and explain the estimates in your own words. Marks: 8 Marks

4) Graph the Total Wealth separately with respect to Age, Employment Status and Education variables and explain the relationship shown in graphs, including the presence of outliers, in your own words. (three separate graphs required). Marks: 8 Marks

5) Use table(s) to explain which year has the highest and lowest average of Total Wealth and highest and lowest standard deviation of Total Wealth. Marks: 8 Marks

6) Run suitable t tests to determine if the difference of Total Wealth between Male and Female is zero, positive and negative (three separate t tests required with null hypothesis: 1. Wealth difference = zero, 2. Wealth difference > zero and 3. Wealth difference < zero) Marks: 12 Marks

7) Present graph and table showing correlation between 'Total Wealth and Income' and 'Age and Education' and discuss the results (provide two correlation measures for two relationships using two variables in each correlation, as mentioned). It is your choice to decide with correlation measure to use (Pearson correlation / Spearman Rank correlation). Explain the reasons and implications of your choice of correlation measure. Marks: 8 Marks

8) Carry out a regression analysis with Total Wealth as dependent variable and Age as independent variable. Discuss the important estimates obtained in regression analysis. Marks: 18 Marks

9) Use the estimates obtained from regression analysis in Part 8 to predict the Total Wealth for individuals with age = 12, 14, 16, 18, 99, 101, 103 and 105 years. Calculate residual errors based on your predicted value and actual given value of Total Wealth for individuals with age = 12, 14, 16, 18, 99, 101, 103 and 105 years. Marks: 12 Marks

10) Comment on the quality of prediction based on the residual errors you obtained in Part 9. Discuss steps you can take to improve the predictions (in other words, reduce the residual errors.) Marks: 12 Marks