Statistics
Regression Analysis
USD 5.00
Learning Objectives:
Upon successful completion of this course, participants will be able to:
- Explain the purpose and applications of regression analysis in analyzing relationships between variables and supporting data-driven decisions.
- Differentiate between simple linear regression and multiple regression models and understand their appropriate applications.
- Interpret regression equations and coefficients to explain how independent variables influence a dependent variable.
- Understand and interpret unstandardized coefficients (B) and standardized Beta coefficients to evaluate the impact and relative importance of predictors.
- Analyze and interpret R² and Adjusted R² values to assess the explanatory power of regression models.
- Interpret hypothesis testing in regression analysis, including p-values, t-tests, and ANOVA results.
- Recognize and assess key regression assumptions, including linearity, independence, homoscedasticity, normality of residuals, and multicollinearity.