1. Do you think Salary is gender-biased?
   1. Run the statistical test of the hypothesis

1. Do you think Salary is City area-dependent?
   1. Formulate the test of equal Salary across all City areas
   2. Run the ANOVA test

1. Do you think the training improves the job satisfaction?
   1. Formulate a statistical test to support your opinion
   2. What is your null hypothesis and what is your alternative hypothesis?
   3. What is your chosen significance level of the test?
   4. Show your test workings
   5. Critically Interpret the test result
   6. Show an alternative way of test.

1. Do you think promotion is gender biased?
2. Create a two-way table of Gender and Promotion.
3. Formulate the statistical test of independence: the null hypothesis and the alternative hypothesis
4. Run the test

1. Relationship between two numerical variables: does salary depend on age?
   1. Create a scatter plot between Age and Salary and interpret the graphs
   2. Run a regression of Salary on Age
2. Relationship among many numerical variables: what determine the JSS after training?
   1. Create 5 scatter plots between Job Satisfaction after Training and the 5 variables: OR, TW, INF, JP, and LWB respectively, and interpret the plots
   2. Run a multiple regression to quantify the influences on the JSS
   3. Interpret the regression output DATA FOR THE TASK (https://docs.google.com/spreadsheets/d/1LIvnyzJy0tFKGG6EKEPoF_4wwqHAymgD/edit?usp=sharing&ouid=107146189620012073874&rtpof=true&sd=true)