Learner Name
In this paper, we will use SPSS 17 Statistical Software to perform various statistical tests on a given data set.
Data File Description
- Describe the context of the data set.
The data set provided is a number of observations of students’ characteristics – from their id number and first/last name to their grades results
- Specify the variables used in this DAA and the scale of measurement of each variable.
There are 21 variables in the data set.
Categorical variables: id, “firstname”, “lastname”, “gender”, “ethnicity”, “lowup”, “section”, “extcr”, “review”, “grade”, “passfail”.
Others are numerical variables
- Specify sample size (N).
The sample size is 105. So, there are 105 student’s observed.
Testing Assumptions
In this paper we will analyze various relationships between “gender” and “gpa” variables. To do this analysis we have to use Student’s t-test.
- Articulate the assumptions of the statistical test.
The assumptions of the t-test for independent samples are normality of the dependent variable and homogeneity of variance. We test these assumptions using SPSS
- Paste SPSS output tests those assumptions and interpret them. Properly embed SPSS output where appropriate. Do not string all output together at the beginning of the section.
- Summarize whether or not the assumptions are met. If assumptions are not met, discuss how to ameliorate violations of the assumptions.
Since p-value of Shapiro-Wilk’s test is higher than 0.05, we can assume the normality of the data. And this assumption is met.
Since p-value of Levene’s test is higher than 0.05, we can treat the group variance as equal. So, the homogeneity of variances assumption is also met.
We are allowed to perform independent sample t-test.
Research Question, Hypotheses, and Alpha Level
- Articulate a research question relevant to the statistical test.
We want to test the claim if there is a significant difference in gpa level between male and female students.
- Articulate the null hypothesis and alternative hypothesis.
H0: μ1=μ2Ha: μ1≠μ2
- Specify the alpha level.
We set alpha level of significance at 0.05
Interpretation
- Paste SPSS output for an inferential statistic and report it. Properly embed SPSS output where appropriate. Do not string all output together at the beginning of the section.
- Interpret statistical results against the null hypothesis.
Since p-value of t-test for equality of means is a little bit higher than 0.05, we failed to reject the null hypothesis.
Conclusion
As we can’t reject the null hypothesis, we have no evidence to claim, that there is a significant difference in gpa between male and female students at 5% level of significance.
- Analyze strengths and limitations of the statistical test.
Independent samples t-test is a very good tool to compare means. As all two assumptions have been met, we may be sure that the results are robust.
References
Not used
