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Regression Analysis Using SPSS
Course Overview
About This Course
Welcome to Regression Analysis Using IBM SPSS Statistics, a comprehensive course designed to help you master one of the most important statistical techniques used for prediction, explanation, and hypothesis testing. Whether you are a student, researcher, academic, or data analyst, this course provides the theoretical foundation and practical skills required to perform and interpret regression analyses using IBM SPSS Statistics.
The course begins with the fundamentals of regression analysis, explaining its purpose, assumptions, and applications across various research disciplines. You will learn how to conduct Simple Linear Regression, Multiple Linear Regression, and Hierarchical Regression Analysis using SPSS. The course covers data preparation, testing model assumptions, interpreting regression coefficients, evaluating model fit, understanding R-squared and adjusted R-squared, assessing multicollinearity, and reporting results according to APA style. Through step-by-step demonstrations and practical examples, you will gain hands-on experience in building, interpreting, and validating regression models for real-world research and data analysis.
By the end of this course, you will have the confidence to perform regression analysis using IBM SPSS Statistics and apply these techniques effectively in academic research, dissertations, theses, business analytics, social sciences, healthcare, and professional data analysis.
Learning Outcomes
Understand the concepts, assumptions, and applications of regression analysis.
Perform and interpret Simple Linear Regression using IBM SPSS Statistics.
Conduct and evaluate Multiple Linear Regression models for prediction and hypothesis testing.
Apply Hierarchical Regression Analysis to assess the contribution of predictor variables.
Report regression analysis results in APA style and research-standard format.
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