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T-Test Application and Interpretation

Coursework Instructions:
Assessment 3 t-Test Application and Interpretation RSCH-FPX7864 - Fall 2025 - Section 07Assessment 3Assessment 3 Instructions Instructions Resources Complete a data analysis report using a t-test for assigned variables Introduction 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 possible differences in final exam scores for students who attended a review session versus students who did not attend a review session. Instructions For this assessment: Use the Data Analysis and Application template (DAA Template [DOCX]). For help with the statistical software, refer to the JASP Step-by-Step: t Tests [PDF] document. View JASP Speedrun: t Test [Video] for a brief tutorial video on this assessment. For information on the data set, refer to the 7864 Data Set Instructions [PDF] document. The grades.jasp file is a sample 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. You will analyze the following variables in the grades.jasp data set: Variables and Definitions Variable Definition Review Attended review sessions? 1 = no; 2 = yes. Final Final exam: number of correct answers. Step 1: Write Section 1 of the DAA: Data Analysis Plan 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: Write Section 2 of the DAA: Testing Assumptions Test for one of the assumptions of t tests – equality (homogeneity) of variances. Create statistical output showing the Levene's Test for Equality Variances. Paste the table in the DAA template. Interpret the Levene's test. Step 3: Write Section 3 of the DAA: Results & Interpretation If the homogeneity assumption is not violated (Section 2), run the “Student” version of the independent samples t-test in the statistical software. If the homogeneity assumption is violated, run the “Welch” version of the independent samples t-test in the statistical software. Also run the “Descriptives” option to obtain the means and standard deviations for each group. Paste the statistical software output of the t test into the DAA template. Below the output: Report the means and standard deviations for each group. State the results of the t test. Interpret the statistical results against the null hypothesis and state whether it is rejected or not 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. 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: Jeffreys's Amazing Statistics Program (JASP). Refer to the Tools and Software: JASP page on Campus for general information. Make sure that your statistical software is downloaded, installed, and running properly on your computer. 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 results and hypotheses. Competency 4: Interpret the results of statistical analyses. Explain statistical conclusions, the limitations of the test, and/or 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.
Coursework Sample Content Preview:
Data Analysis and Application: Independent Sample T-tests Learner Name Capella University Data Analysis and Application: Independent Sample T-test Data Analysis Plan In this paper, the researcher seeks to examine if there is a difference in student performance in the final exams between those who attended review sessions and those who did not attend the review sessions. To achieve this, an independent sample t-test was conducted using the latest version of JASP software. The independent sample t-test is an analytical test that is used to determine whether the mean differences between two groups is significant. The analysis will be guided by the research question: Is there a statistically significant difference in students’ final exam scores between the students who attended review sessions and those who did not attend the reviews? The null hypothesis posits that there is no statistically significant different in final score performance of students who attended review sessions and the ones who did not attend the review. Before the analysis, it is essential to ensure that the data used meet the assumptions required for an accurate independent sample t-test. To run an independent sample t-test, one should have a dichotomous predictor variable with two distinct groups whose membership is mutually exclusive. In the current analysis, the predictor variable is the attendance of a review session with a student either failing to attend the review session or attending the session. The outcome variable in the analysis is the ...
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