Chapter 10 Simple Linear Regression

If the coefficient of correlation (r) = -1.00, then

All the data points must fall exactly on a straight line with a negative slope.

The slope (B1) represents:

change in Y per unit change in X

The ratio of the regression sum of squares (SSR) to the total sum of squares (SST) is called the _____________

coefficient of determination

The strength of the linear relationship between two numerical variables is measured by the:

coefficient of determination

If the p-value for a t test for the slope is 0.021, the results are significant at the 0.01 level of significance (true or false)

false

The value of r is always positive. (true or false)

false

In a simple linear regression model, the coefficient of correlation and the slope:

must have the same sign

One of the assumptions of regression is that the residuals around the line of regression follow the __________ distribution.

normal

In simple linear regression, if the slope is positive, then the coefficient of correlation must also be _______________

positive

The residual represents the difference between the observed value of Y and the __________ value of Y.

predicted

The Y intercept (B0) represents the:

predicted value of Y when X = 0

The change in Y per unit change in X is called the _______

slope

The residuals represent:

the difference between the actual Y values and the predicted Y values.

Which of the following assumptions concerning the distribution of the variation around the line of regression (the residuals) is correct?

the distribution is normal

Assuming a straight line (linear) relationship between X and Y, if the coefficient of correlation (r) equals -0.30:

the slope is negative

In performing a regression analysis involving two numerical variables, you assume:

the variation around the line of regression is the same for each X value

The standard error of the estimate is a measure of:

the variation around the regression line

If no apparent pattern exists in the residual plot, the regression model fit is appropriate for the data. (true or false)

true

If the range of the X variable is between 100 and 300, you should not make a prediction for X = 400. (true or false)

true

Regression analysis is used for prediction, while correlation analysis is used to measure the strength of the association between two numerical variables. (true or false)

true

The coefficient of determination represents the ratio of SSR to SST: (true or false)

true

The regression sum of squares (SSR) can never be greater than the total sum of squares (SST). (true or false)

true

When the coefficient of correlation r = -1, a perfect relationship exists between X and Y. (true or false)

true

If the coefficient of determination (r2) = 1.00, then:

the error sum of squares (SSE) equals 0

The coefficient of determination (r2) tells you:

the proportion of total variation that is explained