Week-2-Statistics-developing-an-understanding-of-the-problem-and-the-data-

Week 2—The assignment for this week involves developing an understanding of the problem and the data that we will be analyzing during the class. We will be using a data set of 50 employees sampled from an imaginary company to answer the question of whether males and females receive equal pay for performing equal work.

The questions in the assignment follow the examples provided in the weekly guidance lectures.

The first question this week focuses on the kind of data we have. Different levels of data allow us to do different kinds of analysis, so we need to understand what we have to work with. Question two involves developing the probability of randomly picking a student who has certain characteristics from the sample.

Question three involves finding the probability of randomly picked employees falling within the top one-third of different groups using Excel functions. Question four and five involve using statistical tests to determine if the compa-ratio (an alternate measure of pay).

The final question asks for an interpretation of your opinion on the question of equal pay for equal work based on the work done this week.

Week 3—During this week, we will look at ways of testing multiple (more than two) data samples at the same time.

We will continue to use the data and assignment file that we opened in Week 2, we just move on to the Week 3 tab.

The first question asks us to determine if the average compa-ratio is equal across 10K salary groups (20 – 29K. 30 – 39K, etc.). The second question asks us to identify which of the salary groups have different averages. The final question asks us to interpret the new information presented in the lecture and assignment; how does the new information we analyzed help us answer our equal pay for equal work question.

Week 4—This week we get to answer our equal pay for equal work question by looking at relationships between and among the different variables.

The first question this week looks at correlations and the creation of a correlation table for our variables. The second question asks for a regression equation showing how the different variables impact the compa-ratio measure. The third questions asks you to discuss the benefits of using a regression equation approach over the single variable tests we have been doing.

The forth question asks for what other information you would have liked to have analyzed in our research. The fifth question asks for your answer to the equal pay for equal work question of: Is the company paying fairly or not? If not, who benefits and why?