Hypothesis Testing Case

Abstract

Researchers are curious about the relationships of various factors. They conduct study's to collect data so they may test and draw conclusions on those relationships. A hypothesis test is used to draw these conclusions.

Hypothesis testing is used by statisticians to test data sets they have collected and report any inferences. Two hypothesis tests were conducted on the intrinsic satisfaction by males in an organization and extrinsic satisfaction by hourly employees, the results are listed below.

Hypothesis Test #1 Intrinsic Satisfaction by Males

Null hypothesis.

Hₒ:µ= 5.0

Alternate hypothesis.

Ha:µ< 5.0

t-Test: Two-Sample Assuming Equal Variances

Male Intrinsic Female Intrinsic

Mean 5.11 5.05

Variance 0.41 0.75

Observations 33.00 33.00

Pooled Variance 0.58

Hypothesized Mean Difference 0.00

df 64.00

t Stat 0.36

alpha 0.05 0.05

P(T<=t) two-tail 0.72

t Critical two-tail 2.00

In the two-tailed hypothesis test the alpha level is 0.05, the test statistic is 0.36 and the critical value is 2.00.

I am failing to reject the null hypothesis statement. The critical value is greater than the test statistic. There is no sufficient evidence that the mean intrinsic score for males is different from 5.0

The fact that the mean intrinsic satisfaction rating for males is not different from 5 communicates to managers that they should try to retain this level of satisfaction among their male employees.

Hypothesis Test #2 Extrinsic Satisfaction by Hourly Employees

Null hypothesis.

Hₒ:µ= 5.0

Alternate hypothesis.

Ha:µ< 5.0

t-Test: Two-Sample Assuming Equal Variances

Hourly Extrinsic Salary Extrinsic

Mean 5.33 5.52

Variance 0.19 0.11

Observations 47.00 19.00