SECTION A: DISCUSSION QUESTIONS

1- Give two examples related to your discipline that you may face imbalance data in classification techniques. How you approach to handle imbalance data? You need to provide detail explanations

2- Explain why you can or why you cannot use R2 or adjusted R2 to evaluate a logistic regression?

3- Give twopractical examples on applications oflogistic regression in your discipline. Provide detail explanations. You need to explain why you think logistic regression can be used in those cases, you do not needto provide data or actually solve them.

4- Assume one of the explanatory variable (named X1) in your logistic regression is a categorical variable with the following levels: low, average, high, very high and another explanatory variable (named X2) is also categorical with the following levels: Sydney, Melbourne and Brisbane. Explain how you will use them in developing your logistic regression model. How many coefficients you will have in your final model?

SECTION B: QUANTITATIVE QUESTIONS

5- There are 500 client records in the first worksheet of theExcel file (provided for this assessment)whohave shopped many special productsfrom an e-Business website. Each record includes data on types of product purchased (between 1-5), purchase amount ($), age, gender, marital status of the customer, whether the client has a membership and whether the customer has a discount card.

a) Explain the steps on how to develop a KNN model to predict which customerswill spend more than $700. (Write your answer as: Step 1-... Step 2- ... and so on. You don't need to run XLMiner and report the results.)

b) Do you think the accuracy of the model will improve if we predict which customers will spend more than $500 rather than $700? Explain the reasons. You don't need to run XLMiner and report the results.

c) Develop a predictive model to predict the spend amount of a new female customer with age of 27 who is married and is not a member and hold a discount card type 3.

6- A company provides maintenance service for washing machines in Victoria.The collected data are presented in the Excel file (second worksheet).

a) Assume the manager asked you to analyse the data and provide him some insights and recommendations. The report should not exceed 2 pages.

b) The managers believe the quality of the parts that are supplied from a supplier is declining over the past few months and that is causing more frequent required service. Perform a predictive analysis to investigate if there is a such relationship.

c) What other data you recommend to the manger to be added into this dataset in future for better analysis and what kind of analysis you think will be useful based on them.

7- In worksheet 3, a dataset from blood bank is presented. The data are recorded for apheresis blood donation made by a group of donors of a period of time. The donor ID is unique for each donor. A donor might have donated more than once in this period. At each donation, the blood total protein level of the donor has been recorded. Use the dataset to answer the following questions:

a) There are some missing values for blood type. Think how you can fill in the missing values. Explain your approach (step by step) and also apply your approach and try to fill the missing value as much as possible in. (save the results in an Excel worksheet in and name it Question 3 Part a.)

b) Calculate the average of total protein for each donor. Explain your approach (step by step). Report them in a worksheet and name it

Question 3 Part b.
c) Calculate the range of total protein for each donor. Explain your approach (steps by step). Report them in a worksheet and name it

Question 3 Part c.
d) Is total protein declining by age?
e) Present two best visualisation tool for this data that you think provide useful information?

8- The data presented in worksheet 4 is the results of a 4-year study conducted to assess how age, weight, and gender influence the risk of diabetes. Risk is interpreted as the probability (times 100) that the patient will have diabetes over the next 4-year period.

a) What predictive model you suggest to relate risk of diabetes to the person's age, weight and the gender. Why?

b) Develop a multiple linear regression model that relates risk of diabetes to the person's age, weight and the gender. Present the regression formula as a mathematical equation. Interpret the significance and coefficients of the regression and comment on the strength of the regression.

c) Develop an estimated multiple regression model that relates risk of diabetes to the person's age, weight, gender and life style. Present the regression formula as a mathematical equation. Interpret the coefficients of the regression and comment on the strength of the regression.

d) What is the risk percentage of diabetes over the next 4 years for a 59-year-old man living in a smalltown with 72 kg weight? Use both models in parts b and c to estimate the risk and compare and comment on the result.

9- Matthewhas a new job as business analyst.He plans to invest 12 percent of his annual salary after the tax into a retirement account at the end of every year for the next 30 years. Suppose that annual return is 5%, and his current after tax salary is 76k which grow 3% per year then:

a) Create a spreadsheet which showsMatthewthe balance of retirement account for various levels of annual investments and returns.

b) If Matthewaims to gain $1,500,000 at the end of the 30th year, what percentage of his salary he should put in the investment annually.

10- FSUB is a companythat intended to introduce its products by advertising them in 3 relevant websites. The names of these websites are noted as A, B and C by the marketing manager of the company. Viewer estimates, cost per advertisement, and maximum usage for each website are as shown:

To ensure a balanced use of advertising, website B advertisements must not exceed 70% of the total number of advertisements authorized. In addition, website A should account for at least 20% of the total number of advertisements authorized.If the budget is limited to $68,000. Note that Website A offers a discount based on the number of orders and Websites B and C do not offer any discount. (Note that for example, if you decide to order 7 advertisements to Website A, the cost to be paid to Website A would be 5*2500+2*2200=16900)

a) How many advertisements should be ordered on each website to maximize total viewers? Write down the models in your report with clear definition of the objective function, constraints and decision variables. Build the models in Excel and save theworksheet (name it Question 6 part a) in the Excel file that you submitting as a part of your exam.

b) Rewrite the model and answer this question: how much Website A must charge per advertisement such that exactly 11advertisements be allocated to website A if the company aim to maximize the total number of viewers? (Assume the cost per advertisement of website B and website C remain the same as presented in the above table).

Attachment:- Datesets.rar