BESC 3010 CH 10 QUESTIONS AND
ANSWERS | LATEST UPDATE |
2024/2025 | RATED A+
What is a regression equation, and what information does it provide?
A regression equation is a mathematical representation of the relationship between a
dependent variable and one or more independent variables, all...
BESC 3010 CH 10 QUESTIONS AND
ANSWERS | LATEST UPDATE |
2024/2025 | RATED A+
What is a regression equation, and what information does it provide?
✔✔A regression equation is a mathematical representation of the relationship between a
dependent variable and one or more independent variables, allowing for predictions and insights
about how changes in the independent variables affect the dependent variable.
How do you interpret the coefficients in a linear regression model?
✔✔The coefficients in a linear regression model represent the expected change in the dependent
variable for each one-unit change in the corresponding independent variable, holding all other
variables constant.
What is the purpose of the R-squared value in regression analysis?
✔✔The R-squared value indicates the proportion of the variance in the dependent variable that is
predictable from the independent variables, reflecting the model's explanatory power.
What does it mean if a regression model has a high standard error?
1
, ✔✔A high standard error indicates that the predicted values from the regression model are
widely dispersed around the actual values, suggesting a poor fit of the model to the data.
How can multicollinearity affect a regression analysis?
✔✔Multicollinearity occurs when independent variables are highly correlated with each other,
which can inflate the standard errors of the coefficients, making it difficult to determine the
individual effect of each variable.
What is the difference between simple linear regression and multiple linear regression?
✔✔Simple linear regression examines the relationship between two variables (one dependent
and one independent), while multiple linear regression assesses the relationship between one
dependent variable and two or more independent variables.
What is the significance of residual analysis in regression?
✔✔Residual analysis involves examining the differences between observed and predicted values
to assess the validity of the regression model, checking for patterns that may indicate model
misfit.
How do you determine if a regression model is statistically significant?
2
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