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Questions and Answers
In simple linear regression, what does the error term ($\epsilon$) account for?
In simple linear regression, what does the error term ($\epsilon$) account for?
- The minimum possible value of the dependent variable.
- The change in the dependent variable for a unit change in the independent variable.
- The variability in the dependent variable not explained by the independent variable. (correct)
- The value of the independent variable when the dependent variable is zero.
Which of the following is NOT an assumption of linear regression?
Which of the following is NOT an assumption of linear regression?
- Homoscedasticity: The errors have constant variance across all levels of the independent variable.
- Multicollinearity: High correlation between independent variables. (correct)
- Linearity: The relationship between the independent and dependent variables is linear.
- Normality: The errors are normally distributed.
In multiple linear regression, what does the coefficient $\beta_i$ represent?
In multiple linear regression, what does the coefficient $\beta_i$ represent?
- The predicted value of the dependent variable when all independent variables are zero.
- The change in the dependent variable for a unit change in $x_i$, holding all other independent variables constant. (correct)
- The standard error of the independent variable $x_i$.
- The change in the independent variable $x_i$ for a unit increase in the dependent variable.
What does the R-squared value measure in regression analysis?
What does the R-squared value measure in regression analysis?
What is the purpose of Adjusted R-squared?
What is the purpose of Adjusted R-squared?
Which plot is commonly used to check for linearity and homoscedasticity in regression analysis?
Which plot is commonly used to check for linearity and homoscedasticity in regression analysis?
What is the primary goal of using a t-test in the context of regression coefficients?
What is the primary goal of using a t-test in the context of regression coefficients?
When is Logistic Regression most appropriate?
When is Logistic Regression most appropriate?
Which of the following is a common solution for addressing heteroscedasticity in a regression model?
Which of the following is a common solution for addressing heteroscedasticity in a regression model?
What is the main purpose of cross-validation in regression model evaluation?
What is the main purpose of cross-validation in regression model evaluation?
Flashcards
Regression Analysis
Regression Analysis
A statistical method to model the relationship between a dependent variable and one or more independent variables.
Simple Linear Regression
Simple Linear Regression
A regression model with one independent variable and one dependent variable, modeled as a straight line.
Intercept (β₀)
Intercept (β₀)
The component in the simple linear regression equation (y = β₀ + β₁x + ε) representing the value of y when x = 0.
Slope (β₁)
Slope (β₁)
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Ordinary Least Squares (OLS)
Ordinary Least Squares (OLS)
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Multiple Linear Regression
Multiple Linear Regression
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R-squared
R-squared
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Adjusted R-squared
Adjusted R-squared
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Residual Analysis
Residual Analysis
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Multicollinearity
Multicollinearity
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