Posted: February 10th, 2015

Dataset for Salary

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This attached document contains salary data for 30 male and 30 female employees at a manufacturing plant. Using the hypothetical dataset, make the following assumptions and answer the questions below.

Assume an equal number of male and female employees at the manufacturing plant and that the salaries of 30 male and 30 female were chosen at random for comparison. Enter the male and female data into separate columns in GraphPad QuickCalcs and perform a t test on the data.
Which form of the t test should you choose for your analysis?
What conclusions can you draw from the results of this analysis?
Now assume that the 30 male and 30 female employees are matched based on the number of years of experience for equivalent work.
Which form of the t test should you choose for your analysis?
Did the assumption of matched participants affect your choice?
What conclusions can you draw from the results of this analysis?
Were the results of this analysis different from the one you did for part A? Why or why not?
Is random assignment always the best way to assign participants to groups? Why or why not?
Is this a true experiment? Why or why not?
Could the dataset used for this project be from an experiment? 
OR 
Could the dataset used for this project be from an ex post facto study?

Write a description of procedures that make this dataset appear to be from a true experiment. Then write a description of procedures that make this dataset appear to be from an ex post factor study

Data Information
Male Female
29300 28800
31500 31600
30400 29800
28500 28500
33500 32600
27800 28000
29500 29200
31200 30100
28400 28200
29200 28500
28420 28570
28480 27650
34240 34370
28770 28700
30360 29090 T.TEST(A2:A31,B2:B31,2,2)
29990 29530
36690 33480
29740 29900
30490 30470
28470 27500
28950 28830
28430 27470
32220 32230
33040 33230
31050 31090
28600 28780
31820 32000
28950 26990
32120 32310
28450 28510

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