• module_7_ASSIGN.xlsx (20.477 KB)

Attached is an Excel spreadsheet, listing data for the Acme Widget company, specifically their salary ranges broken down by sex (male/female). Use that data to investigate the claim that women in that company make less money, on average, than men.Note that the spreadsheet data is sorted by sex to make it easy to find the mean or median salary category for males and females separately. write awritten report that looks and reads as professional as possible. The report should be written in Microsoft Word;save your document anduploadas usual it by clicking on the heading of this assignment and send the Word document to me as an attachment. To guide you in writing the report - which should be about 1 or 2 pages long - make sure to:

• Mention some general facts about your data set, such as where you got it from, whether it's a sample or the entire population, and what the sample size is.
• Next, you should describe the variables you are interested in, and list some of their statistics, such as how many men and women are in your data, total sample size, type of variable, etc.
• You should then formulate your hypothesis and supply data to support it. For example, you could compute mean, mode, and/or median for your data, if appropriate. Depending on whether they are similar or different for the male and female portion of your data, different hypothesis would be supported. But note that comparing two means alone does notproveany conclusive relationship between them.
• You need to compute a contingency table with the associated p-valueto support your conclusions, as described in section 4.Only this p-valuecan be used to determine whether there is a relationship between two variables! As is often the case, you could us Excel or StatCrunch (use "Stat | Tables | Contingency | with Data") to find the p-value, with StatCrunch being the easier method. Also, once you have evidence for a relationship, you need to determine which way the relationship goes.

As to what I consider a "professional" report: anything that (1) has a suitable introduction, (2) makes a clear statement as to what you are claiming, (3) has data to support your claim, (4)includesa chart, table, or diagram to visualize your claim(s), and (5) has a concise conclusion. Note that it's completely easy to "copy-and-paste" tables or charts, sodo notfill up your report with charts that you really do not need for your argument. Only add relevant chartsto your report.Note also that the "salary" appears in two columns, once with actual labels in the "Salary Level" column, and the other one with a corresponding " Salary Code". You can use the column with the labels to create a "Pivot Table" (Excel) or "Contingency Table" (StatCrunch) and conduct the required Chi-Square test, while you can use the numeric code to compute, for example, the mean salarycategory(which is not the same as the mean salary!). But, you could just as well ignore the code and work directly with the categories, the Pivot or Contingency Table, and the Chi-Square tes