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5 pages/≈1375 words
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APA
Subject:
Accounting, Finance, SPSS
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English (U.S.)
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Topic:
Multiple Regression in SPSS
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Good evening, I wanted to make sure that I selected the correct time/date because when I looked back at it, it was showing a date of 3/17/25 when in fact I should be 3/16/25. Can you confirm that it will be completed today?
In this week, you will conduct a multiple regression analysis using one of the datasets provided by your instructor. If you have previously completed the Quantitative Reasoning and Analysis course here at Walden University, you should not turn in a paper you submitted in an earlier course or use the same variables that you used to conduct a multiple regression. Please note that SafeAssign will match your assignment to your submission(s) from the earlier course and it is not permissible to reuse work from previous courses without specific permission from your instructor.
To prepare for this Assignment:
Review this week’s Learning Resources and media program related to multiple regression.
Based on the dataset you chose, construct a research question that can be answered with a multiple regression analysis.
By Day 7
Write a 1- to 2-page analysis of your multiple regression results, addressing each research question. In your analysis, display the data for the output. Based on your results, provide an explanation of what the implications of social change might be.
Use proper APA format, citations, and referencing for your analysis, research question, and display of output.
Datasets
In this course, your instructor will provide you with one dataset (Guided Sample Dataset: Statistics Anxiety) that will be used in several of the tutorial videos. You are encouraged to reproduce the analyses performed in the video using this dataset so you can compare your answers and check your understanding of how to do each analysis in SPSS. You will also be provided with three large datasets for you to use in application of the statistics you're learning each week. The Statistics Anxiety dataset is not for use in your weekly Assignments. Your instructor may also recommend using a different dataset from the ones we have provided here, which is fine. Your instructor will share these datasets in the Doc Sharing section of the classroom and as an Announcement
(GUIDED SAMPLE DATASETS WILL BE UPLOADED)
References:
Warner, R. M. (2021) Applied statistics II: Multivariable and multivariate techniques (3rd ed.). SAGE Publications
Chapter 5, "Multiple Regression with Multiple Predictors" (pp. 133 - 186).
Chapter 5 of Warner might seem like a giant leap forward at this point in the course but do not worry. It is a natural progression from the regression you learned in the previous quantitative analysis course, and it explains in straightforward language how to shift your thinking to work with regression models with more than two predictor variables.
Walden University Library. (2016). Article critique assignment guideLinks to an external site.. Retrieved from http://academicguides(dot)waldenu(dot)edu/rsch8260/week2assignment
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Analysis of the Moderating Role of Gender in the Relationship Between Motivation and GPA
Your Name
Subject and Section
Professor’s Name
March 17, 2025
Multiple Linear Regression
This study investigates whether Gender moderates the relationship between Motivation and academic performance, as measured by GPA. The research question is: "Does gender influence the relationship between motivation and GPA among students?" A moderated multiple regression analysis was conducted to examine this potential interaction effect.
Methods
The research data consisted of 335 students and measured GPA (dependent variable), Motivation Score (independent variable), and Gender (moderator). The described interaction term consisted of Centered Motivation as a precentering step, and this product united with the Gender variable. The two models represented the multiple regression analysis. The first model assessed the main effects of Motivation and Gender and their impact on GPA. The second model integrated the interaction term for moderation testing.
Results
A summary of multiple regression statistics includes the following points. The analysis of Model 1 produced main effects with a negligible R² value of 0.002, which yielded F(2,332) = 0.334 p = 0.716. The second regression model with an interaction term reached an R² value of 0.002 but proved insignificant because F(3,331) = 0.233 and p = 0.873. An evaluation of the interaction term against GPA data showed no significant contribution (p = 0.854) to the explained variance.
All predictors in the analysis were statistically insignificant based on the results. The analyzed coefficients of B = 0.000 and p = 0.870 indicated that tests showed this variable was insignificant. A non-significant association was det...
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