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Regression Analysis
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Learning Material
Title
Volume
Introduction to Regression Analysis: An overview of regression analysis, its applications, and the basic concepts involved in the regression model.
5.89 MB
<p>Introduction to Regression Analysis: An overview of regression analysis, its applications, and the basic concepts involved in the regression model.</p>
Simple Linear Regression: Exploring the fundamentals of simple linear regression, including the least squares method, interpretation of coefficients, and model assumptions.
5.89 MB
<p>Simple Linear Regression: Exploring the fundamentals of simple linear regression, including the least squares method, interpretation of coefficients, and model assumptions.</p>
Model Assumptions and Diagnostics
5.89 MB
<p>Model Assumptions and Diagnostics: Examining the assumptions underlying regression models, such as linearity, independence, homoscedasticity, and normality. Diagnostic techniques for model validation are also covered.</p>
Multiple Linear Regression
5.89 MB
<p>Multiple Linear Regression: Extending the concepts from simple linear regression to multiple predictors, including interpretation of coefficients, multicollinearity, and model evaluation.</p>
Variable Selection and Model Building
5.89 MB
<p>Variable Selection and Model Building: Strategies for selecting relevant predictors and building regression models, including stepwise regression, forward and backward selection, and model selection criteria.</p>
Model Interpretation and Inference: Techniques for interpreting regression coefficients, conducting hypothesis tests, and constructing confidence intervals.
5.89 MB
<p>Model Interpretation and Inference: Techniques for interpreting regression coefficients, conducting hypothesis tests, and constructing confidence intervals.</p>
Residual Analysis: Analyzing residuals to assess model adequacy, detect outliers, and identify influential data points.
5.89 MB
<p>Residual Analysis: Analyzing residuals to assess model adequacy, detect outliers, and identify influential data points.</p>
Advanced Topics in Regression Analysis
5.89 MB
<p>Advanced Topics in Regression Analysis: Depending on the course, this chapter might cover advanced topics such as logistic regression, generalized linear models, time series regression, and hierarchical regression.</p>
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