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Week 1 Assignment


We have 3 primary goals this week – introduce and understand the research issue we will use as a base to master statistical techniques, discover how we describe and summarize data sets, and examine some basics of probability – particularly probabilities based on the normal curve. Statistics is typically taught with different problems at the end of each chapter. Take a look at our text as an example. While this is ok for learning how to use each tool, it is not an effective way to let us compare and contrast the different tools, and the way each tool/technique provides us with different information about the data set. Instead of using this approach, we will have a single data set to use as we attempt to use the data to answer a single question. The data set we will be using consists of different salary related measures for a sample of 50 employees from a fictitious company. The question we are trying to answer is “do males and females get equal pay for equal work?” The data we have to work with includes: ID – a number assigned to distinguish between the different employees in the sample Salary – the annual pay an employee receives, rounded to the nearest thousand dollars Compa – the salary divided by the midpoint of the pay grade the employee is in; this is a common compensation measure showing where an employee is within each pay grade Midpoint – the dollar amount (rounded to the nearest thousand dollars) that is in the middle of the pay grade Age – the employee’s age (rounded to the nearest birthday) Performance rating – a value between 1 and 100 showing the manager’s rating how good the employee performs their job Service – the years the employee has been with the company (rounded to the nearest hiring anniversary Gender – a numerical code indicating the employee’s gender (1 = female, 0 = male) Raise – the percent increase in pay of the last performance based increase in salary Degree – the educational achievement of the employee (0 = BA/BS, 1 = Master’s or more) Gender1 – a letter code indicating the employee’s gender (F = female, M = male) Grade – the employee’s pay level – grade A is the lowest (entry level) and grade E is the highest.


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