AP Stats Chapter 12

Front

What is a residual plot?

Back

A residual plot is a graph that shows the residuals on the vertical axis and the independent variable on the horizontal axis. It helps to assess the fit of a regression model.

Front

What does a strong correlation coefficient indicate?

Back

A strong correlation coefficient (close to 1 or -1) indicates a strong linear relationship between two variables.

Front

What is the interpretation of a slope in a linear regression model?

Back

The slope represents the average change in the response variable for each one-unit increase in the explanatory variable.

Front

What does the term 'degrees of freedom' refer to in regression analysis?

Back

Degrees of freedom in regression analysis refer to the number of independent pieces of information available to estimate parameters, typically calculated as the number of observations minus the number of parameters estimated.

Front

What is the purpose of a scatterplot in regression analysis?

Back

A scatterplot visually represents the relationship between two quantitative variables, helping to identify patterns, trends, and potential outliers.

Front

What does it mean if a residual plot shows a random scatter?

Back

A random scatter in a residual plot suggests that the regression model is appropriate and that the assumptions of linear regression are met.

Front

How do you interpret the y-intercept in a linear regression equation?

Back

The y-intercept represents the predicted value of the response variable when the explanatory variable is zero.

Front

What is the formula for a simple linear regression model?

Back

Front

What does it mean if a plot of log(y) against x is linear?

Back

If a plot of log(y) against x is linear, it indicates that the relationship between y and x is exponential.

Front

What is the significance of the R-squared value in regression analysis?

Back

The R-squared value indicates the proportion of variability in the response variable that can be explained by the explanatory variable(s).