Regression Model
Definition
A regression model is a statistical tool used to examine the relationship between a dependent variable and one or more independent variables. It helps us understand how changes in the independent variables affect the dependent variable.
Analogy
Think of a regression model as a recipe for baking cookies. The ingredients (independent variables) like flour, sugar, and butter are combined in specific quantities to create the final product (dependent variable), which is the delicious cookie. By adjusting the amounts of each ingredient, we can see how it affects the taste and texture of the cookie.
Related terms
Predictor Variables: These are the independent variables in a regression model that are used to predict or explain changes in the dependent variable.
Coefficient: In a regression model, coefficients represent the estimated change in the dependent variable for each unit change in an independent variable.
Residuals: Residuals are the differences between observed values and predicted values from a regression model. They help assess how well the model fits the data.
"Regression Model" appears in:
Study guides (2)
Practice Questions (10)
- If the confidence interval for the slope of a regression model is (-0.5, 1.2), what can we conclude?
- If the confidence interval for the slope of a regression model is (-2.3, -0.7), what can we conclude?
- As sample size increases what happens to the width of the confidence interval for the slope of a regression model?
- If the confidence interval for the slope of a regression model is (-0.3, 0.3), what can we conclude?
- Suppose a 99% confidence interval for the slope of a regression model is (0.2, 0.8). What can we infer about the precision of the estimate?
- What formula is used to compute the t-score for testing the slope of a regression model?
- What are the degrees of freedom for the t-distribution when testing the slope of a regression model with only one parameter?
- What is the purpose of the degrees of freedom in a t-test for the slope of a regression model?
- When is it appropriate to exclude an influential point from a regression model?
- When selecting a transformation for a regression model, what should be considered?
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