I submitted this assignment but was incorrect in one of these 3 areas. I am not sure which one i am incorrect in. Step 2: Testing Assumptions: Test for one of the assumptions of t-tests—homogeneity of...

I submitted this assignment but was incorrect in one of these 3 areas. I am not sure which one i am incorrect in.

Step 2: Testing Assumptions:

Test for one of the assumptions of t-tests—homogeneity of variance.

• Interpret the Levene's test.

Step 3: Results and Interpretation

• Report the means and standard deviations for each group.


• State the results of the t-test using the "Assume equal variances" row.


• Interpret the statistical results against the null hypothesis and state whether it is accepted or rejected.

Step 4: Statistical Conclusions

• Provide a brief summary of your analysis and the conclusions drawn about this t-test.

Running head: DATA ANALYSIS AND APPLICATION TEMPLATE 1 PAGE 2 Data Analysis and Application Capella University Data Analysis Plan In assignment 3, the variables being used to conduct the Levene test and t-Test are Gender and GPA. While performing the Levene test and T-Test Gender was defined as female or male, and GPA was defined as the previous grade point average. Gender is classified as categorical data while GPA is classified as continuous data in this assignment. Does a difference exist between females and males for previous grade point averages? The null hypothesis states there is not a difference between females and males for previous grade point averages. The alternative hypothesis states that there is difference between females and males previous grade point averages Testing Assumptions The data presented from the Levene and T-test indicates that the assumption of homogeneity of variances is met. The Levene test shows F= .095, p= .758 were the p-value is not less than .05. Due to the p-value being greater than .05 we do not reject the null hypothesis. Results and Interpretation Group Statistics gender N Mean Std. Deviation Std. Error Mean gpa 1 64 2.9719 .67822 .08478 2 41 2.6910 .73942 .11548 From the descriptive statistics output, it is found that mean and standard deviation of females are 2.9719 and 0.67822 respectively and for males it is 2.6910 and 0.73942. From the data analysis preformed it displayed that there is not a significant difference in the means of female students GPA (M= 2.97; SD= .67) and male students GPA (M= 2.69; SD= .73). From the data table we see that the T-test shows t(103)=1.9, p= .14 with the p=value not being less than .05. Therefore, since the p-value is greater than .05 we do not reject the null hypothesis. From "Assume equal variances" row for the two-sample t test in the above SPSS output, the p value of the test is obtained as 0.048 which is less than 0.05. Therefore, the null hypothesis is rejected, and it can be concluded that there is a significant difference in the GPA between Male and Female”. Statistical Conclusions The Levene test shows F= .095, p= .758 were the p-value is not less than .05 and the -test shows t(103)=1.4, p= .048 with the p=value not being less than .05. Due to the p-value for both tests not being less than .05 we do not reject the null hypothesis that states that there is no significant difference between means for female and male GPAs. Independent samples T-test has limitations include we cannot test more than two different groups at a time. In a T-test there can only be one independent variable and one dependent variable being tested. Sample size is another limitation, larger sample sizes are a more accurate representation of the population. If data is violated by the assumption the t-test may not have reliability. For future areas of exploration, the GPA and final or GPA and final grade would be areas that would perhaps generate information into students GPA and student’s final grades in the course. Also, how male and female students did per test may provide information as well. Application In the field of residential treatment this type of test may assist with illustrating the difference between male and female and self-esteem. Do men and women in our program have different average amounts of self-esteem? In the program I work in we build residents confidence and hopes this confidence will transfer to other areas of life. Hopefully feeling confident in advocating for themselves. Using this test, we can see the difference and perhaps change our program accordingly. I have always wanted to have a men’s group and women’s group that focused on different issues according to gender. References Field, A. (2018). Discovering Statistics Using Ibm Spss Statistics: North American edition. SAGE.