1. Introduction– Introduce the business problems.

Question

i. Describe the main objectives of the researchers who collected this dataset

ii. Describe how you want to achieve these objectives in this assignment

iii. List all statistical hypotheses you want to test in this assignment and indicate how the hypotheses are related to the research objective above.

(Note: you can put the hypotheses you are going to test in a table with names of the tests and purpose of the tests) (8 marks)

Hint: you should write this section after you finish all the following tasks.

2. Do you think Salary is gender-biased?

i. Formulate a statistical hypothesis to test the gender-unbiasedness of payment

ii. Run the statistical test of the hypothesis

iii. Conclude your test result

3. Do you think Salary is City area-dependent?

i. Formulate the test of equal Salary across all City areas

ii. Run the ANOVA test

iii. Interpret your results

4. Do you think the training improves the job satisfaction?

i. Formulate a statistical test to support your opinion

ii. What is your null hypothesis and what is your alternative hypothesis?

iii. What is your chosen significance level of the test?

iv. Show your test workings

v. Critically Interpret the test result

vi. Show an alternative way of test.

5. Do you think promotion is gender biased?

I. Create a two-way table of Gender and Promotion.

II. Formulate the statistical test of independence: the null hypothesis and the alternative hypothesis

III. Run the test

IV. Interpret the results

6. Relationship between two numerical variables: does salary depend on age?

i. Create a scatter plot between Age and Salary and interpret the graphs

ii. Run a regression of Salary on Age

iii. Interpret the regression output

7. Relationship among many numerical variables: what determine the JSS after training?

i. Create 5 scatter plots between Job Satisfaction after Training and the 5 variables: OR, TW, INF, JP, and LWB respectively, and interpret the plots

ii. Run a multiple regression to quantify the influences on the JSS

iii. Interpret the regression output