Hypothesis Testing With Sun Coast Remediation Data Set

Running Head: HYPOTHESIS TESTING WITH SUN COAST REMEDIATION DATA SET
Title: Hypothesis Testing with Coast Remediation Data Set
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2
Independent Samples
t-Test:
Null hypothesis: H01: There is no statistically significant difference between average
“Group-A Prior Training Scores” and “Group-B Revised Training Scores”.
Alternate hypothesis: HA1: There is statistically significant difference between
average “Group-A Prior Training Scores” and “Group-B Revised Training Scores”.
Table 1: Excel Output of Independent t-test with Unequal Variances
Results:
Average training score of Group-B (M = 84.77, SD = 5.19) was higher than average
score of training score of Group-A (M = 69.79, SD = 11.05). The results of the two-tailed
independent t-test indicates that the p-value < 0.01, implying average revised training score
of Group-B is significantly different (higher) than prior training scores of Group-A at α =
1% level of significance. Hence, the null hypothesis assuming the equality between the
average scores of the two groups is rejected against the alternate hypothesis at α = 1%
level of significance. Therefore, it can be concluded that average revised training scores for
Group-B is significantly higher than average prior scores of Group-A (Lakens, 2017).