Assessment 3 Instructions: t-Test Application and Interpretation

• Complete an SPSS data analysis report using a t-test for assigned variables.In this assessment, you’ll begin to explore mean group differences in your courseroom data. Is it possible that being in a particular group results in higher or lower mean achievement levels? You’re going to explore gender differences and overall learner GPA.
  

  INSTRUCTIONS

  Complete this assessment using the Data Analysis and Application Template [DOC](also known as the DAA Template).

  • Refer to IBM SPSS Step-By-Step Guide: t-Tests [PDF] for additional information on using SPSS for this assessment.
  • Review the Copy/Export Output Instructions [PDF] for help copying SPSS output into your DAA Template.
  • Use the Data Set Instructions [PDF]for information on the data set.
  • Refer to the Course Study Guide [PDF] for information on analyses and interpretation.

  The grades.sav file is a sample SPSS data set. The data represent a teacher’s recording of student demographics and performance on quizzes and a final exam across three sections of the course. Each section consists of 35 students (N = 105). There are 21 variables in grades.sav.You will analyze the following variables in the grades.sav data set:

  SPSS Variables and Definitions

  SPSS Variable	Definition
  Gender	female = 1; male = 2
  GPA	previous grade point average

  Step 1: The Data Analysis Plan

  In Step 1:

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

  Step 2: Testing Assumptions:

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

  • 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 Template.
  • Interpret the Levene’s test.

  Step 3: 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: Statistical Conclusions

  In Step 4:

  • 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: Application

  In Step 5:

  • 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.

  Submit your DAA Template as an attached Word document in the assessment area.

  SOFTWARE

  The following statistical analysis software is required to complete your assessments in this course:

  • IBM SPSS Statistics Standard or Premium GradPack, version 24 or higher, for PC or Mac.

  You have access to the more robust IBM SPSS Statistics Premium GradPack.Please refer to the Statistical Software page on Campus for general information on SPSS software, including the most recent version made available to Capella learners.Make sure that your SPSS software is downloaded and installed with fully activated licensing on your computer and running properly within your operating system (PC or Mac). If you need help with these steps, refer to the SPSS Installation Helper.

  COMPETENCIES MEASURED

  By successfully completing this assessment, you will demonstrate your proficiency in the course competencies through the following assessment scoring guide criteria:

  • Competency 1: Analyze the computation, application, strengths, and limitations of various statistical tests.
    • Analyze statistical assumptions.
  • Competency 2: Analyze the decision-making process of data analysis.
    • Articulate the data analysis plan.
  • Competency 3: Apply knowledge of hypothesis testing.
    • Interpret statistical resultsand hypotheses.
  • Competency 4: Interpret the results of statistical analyses.
    • Explain statistical conclusions, the limitations of the test, and possible alternative explanations.
  • Competency 6: Apply the results of statistical analyses (your own or others’) to your field of interest or career.
    • Analyze the potential applications of the test in the field and their implications.
  • Competency 7: Communicate in a manner that is scholarly, professional, and consistent with the expectations for members in the identified field of study.
    • Communicate in a manner that is scholarly, professional, and adheres to APA style and formatting.

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