.

Tuesday, September 24, 2019

Final Project Statistics Example | Topics and Well Written Essays - 1000 words

Final - Statistics Project Example The interest of the study is to test if there is any significance difference between the energy intake before and after the exercise session. The most appropriate test for this study is the paired sample t-test. The test determines if there is significant difference between average values of measurements taken from a sampling unit under two different conditions (Park, 2009). The test is based on the paired difference between the two measurements. This is a two tailed test where both variables are dependent variables, i.e. pre and post-test variables. The power and post hoc testing for this study will be Bonferroni and Turkey’s test. Bonferoni is the simplest post hoc test because of its flexibility and ability to be used as correction test (Pavlidis, n.d). Bonferroni calculates the new pairwise alpha to be compared with the initial alpha . Bonferroni alpha is calculated as Pretessting and posttessting data both seem to be normally distributed. The conclusion is supported by Shapiro wilk test for normality. This test was chosen since it works best for a smaller samples size of less than 50. The results were as follows; From Shapiro wilk test, both pretesting and posttesting data was normally distributed. The significance values 0.803 and 0.712 are both greater than alpha 0.05. This test confirms that the data is appropriate for a paired t-test. In this study, there were 20 people whose energy intake was examined before and after going to the gym. The average energy intake before the exercise sessions was 6650.7 with a standard deviation of 1495.704 while the energy intake after the session was 5304 with a standard deviation of 1518.826. The last column gives the standard error of the mean for each of the test. This output also shows that there were 20 pairs of observation in the study. The correlation between variables in given in column three i.e . The fourth column shows the p value for the correlation coefficient. With an

No comments:

Post a Comment