Common Assessment #4

Front

What is a linear regression model?

Back

A linear regression model is a statistical method used to model the relationship between a dependent variable (y) and one or more independent variables (x) by fitting a linear equation to observed data.

Front

What does a positive correlation coefficient indicate?

Back

A positive correlation coefficient indicates that as one variable increases, the other variable also tends to increase, showing a positive linear relationship.

Front

What does a negative correlation coefficient indicate?

Back

A negative correlation coefficient indicates that as one variable increases, the other variable tends to decrease, showing a negative linear relationship.

Front

What is the formula for a linear function?

Back

Front

What does the slope of a linear function represent?

Back

The slope of a linear function represents the rate of change of the dependent variable (y) with respect to the independent variable (x).

Front

What is a residual in the context of linear regression?

Back

A residual is the difference between the observed value and the predicted value of the dependent variable in a regression model.

Front

What does it mean if two linear functions have no points of intersection?

Back

If two linear functions have no points of intersection, it means they are parallel lines and have the same slope but different y-intercepts.

Front

How do you determine if a linear model is a good fit for data?

Back

A linear model is a good fit for data if the residuals are randomly distributed and there is a strong correlation between the independent and dependent variables.

Front

What is the significance of the y-intercept in a linear equation?

Back

Front

What is the difference between a strong and weak correlation?

Back

A strong correlation means that the data points are closely clustered around the line of best fit, while a weak correlation indicates that the data points are more spread out.