Unit 2: Exploring Two-Variable Data

If [math] for a linear regression model, this means:

The least-squares regression line is the line that:

A residual is defined as:

If a residual plot shows a clear curved pattern, this suggests that:

An influential point in regression is a point that:

The regression line [math] predicts that for every one-unit increase in [math]:

Extrapolation in regression is risky because:

A correlation of [math] indicates:

The correlation coefficient between two variables is r = −0.85. Which of the following is the best interpretation?

If the correlation between hours studied and test score is r = 0.80, what proportion of the variation in test scores is explained by hours studied?

A least-squares regression line predicts ŷ = 72 for a given x value. The actual observed value is y = 78. What is the residual?

The regression equation for predicting weight (in pounds) from height (in inches) is ŷ = −150 + 4.5x. Which is the best interpretation of the slope?

A regression model is built using data where x ranges from 10 to 50. Using this model to predict y when x = 80 is called:

A study finds a strong positive correlation between ice cream sales and drowning rates. What is the most likely explanation?

A student scores 2 standard deviations above the mean on a first test. On a retest, the student is most likely to score:

A residual plot shows a clear curved pattern. This suggests that:

Which of the following statements about the correlation coefficient r is TRUE?

If a scatterplot of x vs. y shows an exponential pattern, which transformation might linearize the relationship?

In the regression equation ŷ = 12 + 3x, the y-intercept 12 means:

The standard deviation of the residuals (s) in a regression measures: