* A department head wants to compare the performance of her morning team versus her afternoon team. The morning team has 6 staffs while the afternoon team has 5 staffs. To keep things fair, both groups were given identical computer sets with respect to specifications. She is interested in knowing whether the average mean time of the morning team is not equal to the average mean time of the afternoon team. The data is given below. Morning Team Afternoon Team 40.0 75.5 47.3 69.1 64.2 62.3 72.3 53.9 38.2 58.4 46.8Null Hypothesis: There is significant difference between the mean time of O morning team and afternoon team. Alternative Hypothesis: There is no significant difference between the mean time of morning team and afternoon team. Null Hypothesis: There is no significant relationship between the mean time O of morning team and afternoon team. Alternative Hypothesis: There is significant relationship between the mean time of morning team and afternoon team. Null Hypothesis: There is no significant difference between the mean time of O morning team and afternoon team. Alternative Hypothesis: There is significant difference between the mean time of at least one member of morning team and one member of afternoon team. Null Hypothesis: There is no significant difference between the mean time of O morning team and afternoon team. Alternative Hypothesis: There is significant difference between the mean time of morning team and afternoon team.O t-test Concerning Means of Independents Samples O Z-test on the Significance of Difference between the Population and a Sample Proportion O Z-test on the Comparison between the Population Mean and Sample Mean ANOVA O t-test on the Comparison between the Population Mean and the Sample Mean O z-test on the Significance of Difference between Two Independent Proportions O t-test on the Significance of the Difference Between Two Correlated Means