Reference no: EM13245119
Below are 2 one-sample t-tests comparing male and female average salaries to the overall sample mean.
Based on our sample, how do you interpret the results and what do these results suggest about the population means for male and female salaries?
Males Females
Ho: Mean salary = 45 Ho: Mean salary = 45
Ha: Mean salary =/= 45 Ha: Mean salary =/= 45
Note when performing a one sample test with ANOVA, the second variable (Ho) is listed as the same value for every corresponding value in the data set.
t-Test: Two-Sample Assuming Unequal Variances t-Test: Two-Sample Assuming Unequal Variances
Since the Ho variable has Var = 0, variances are unequal; this test defaults to 1 sample t in this situation
Male Ho Female Ho
Mean 52 45 Mean 38 45
Variance 316 0 Variance 334.6666667 0
Observations 25 25 Observations 25 25
Hypothesized Mean Difference 0 Hypothesized Mean Difference 0
df 24 df 24
t Stat 1.968903827 t Stat -1.913206357
P(T<=t) one-tail 0.03030785 P(T<=t) one-tail 0.033862118
t Critical one-tail 1.71088208 t Critical one-tail 1.71088208
P(T<=t) two-tail 0.060615701 P(T<=t) two-tail 0.067724237
t Critical two-tail 2.063898562 t Critical two-tail 2.063898562
Conclusion: Do not reject Ho; mean equals 45 Conclusion: Do not reject Ho; mean equals 45
Based on our sample results, perform a 2-sample t-test to see if the population male and female salaries could be equal to each other.
Based on our sample results, can the male and female compas in the population be equal to each other? (Another 2-sample t-test.)
What other information would you like to know to answer the question about salary equity between the genders? Why?
If the salary and compa mean tests in questions 3 and 4 provide different results about male and female salary equality,
which would be more appropriate to use in answering the question about salary equity? Why?
What are your conclusions about equal pay at this point?
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