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T-Test Application And Interpretation


T-Test Application And Interpretation

T-Test Application And Interpretation


Step 1: Write Section 1 of the DAA: The Data Analysis Plan

  • Name the variables used in this analysis and whether they are categorical or continuous.
  • State a research question, null hypothesis, and an alternate hypothesis for the independent samples t-test.

Step 2: Write Section 2 of the DAA: Testing Assumptions

  • Create SPSS output showing the Levene’s Test for Equality Variances. Run the Levene’s test on the dependent variable test for the entire sample. Do not split the data up by gender before running the homogeneity test.
  • Paste the table in the DAA.
  • Interpret the Levene’s test.

Step 3: Write Section 3 of the DAA: Results and Interpretation

Paste the SPSS output of the t test. Below the output:

  • 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: Write Section 4 of the DAA: Statistical Conclusions

  • Provide a brief summary of your analysis and the conclusions drawn about this t-test.
  • Analyze the limitations of the statistical test and/or possible alternative explanations for your results.

Step 5: Write Section 5 of the DAA: Application

  • Analyze how you might use the independent samples t-test in your field of study.
  • Name an independent variable and dependent variable that would work for such an analysis and why studying it may be important to the field or practice.
  • attachmentBook1.xlsx
  • attachmentGraphs.docx
  • attachmentindependentsamplet-test1.docx


Group Statistics
 genderNMeanStd. DeviationStd. Error Mean
 Levene’s Test for Equality of Variancest-test for Equality of Means
gpaEqual variances assumed.112.7391.462103
 Equal variances not assumed  1.46185.248
t-test for Equality of Means
tdfSig. (2-tailed)Mean DifferenceStd. Error Difference95% Confidence Interval of the Difference

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