2 Running Head: STATISTICS PROJECT Statistics Project: Part II Carla Pinkney PSYCH/625

2
Running Head: STATISTICS PROJECT
Statistics Project: Part II
Carla Pinkney
PSYCH/625
August 9, 2021
Mr. Matt Will
Statistics Project
From the dataset provided, a lot of hypotheses can be formulated. For example, given the dataset, one can hypothesize the happiness rating between males and females or workplace engagement between males and females. For example, consider the following hypothesis below.
Null Hypothesis: There is statistical significance in the workplace engagement rating between male and female
Alternative Hypothesis: There is a statistically significant difference in the workplace engagement rating between males and females.
In order to determine whether there exists a statistically significant difference in the workplace engagement rating between males and females, an independent t-test will be used. This is because, workplace engagement rating between the two groups, male and female, is independent of each other and thus suitable to use an independent t-test. Scholars have outlined several steps to follow when carrying out an independent t-test. According to Jackson (2017), one has to run an F test to determine the equality of variance between the two groups before proceeding to run an independent t-test.
Null Hypothesis: There is no statistically significant difference between the variance of the two groups
Alternative Hypothesis: There is a statistically significant difference between the variance of two groups
Consider the output for the F test for equality of variance below;
From the test of equality of variance, the p-value of 0.4242, which is greater than 0.05, indicates that we accept the null hypothesis and conclude that there is no statistically significant difference in the variance of two groups at a 5% level of significance. After confirming that the two groups have equal variance, one can run an independent t-test to establish whether there is a difference in workplace engagement rating between males and females, assuming equal variance between the two groups. Some studies, however, found that there exists a disparity in workplace engagement between males and females. According to a study done by “Advisa Web Team” (2016) on workplace engagement and gender, it was found that females were highly engaged at the workplace as compared to men. Consider the output below for the independent t-test;
From the output above, the p-value for the one-tailed independent t-test is given as 0.162599, and the two-tailed independent t-test is given as 0.3252, which are greater than 0.05. This implies that we fail to reject the null hypothesis and conclude that there is no statistically significant difference in the workplace engagement rating between males and females at a 5% level of significance.
References
Jackson, S. L. (2017). Statistics: plain and simple. Cengage Learning.
Advisa Web Team. (2016, November 3). Fast Facts: Engagement and Gender – ADVICE. ADVISA. https://www.advisausa.com/2016/11/fast-facts-engagement-gender/