Analyzing Two Variable Data

What would happen to the correlation if the time was measured in days rather than in weeks?

• The correlation would stay the same because changing the units of measurement does not change the correlation.

• The correlation would change because changing the units of measurement changes the correlation.

  
  

• The correlation would stay the same because it does not distinguish between the explanatory and response variables.

• The correlation would change because it distinguishes between the explanatory and response variables.

Which best describes the form of this scatterplot?

• linear

• nonlinear

• scattered

• no correlation

What would happen to the correlation if the average test score was on the horizontal axis and the study time was on the vertical axis?

• The correlation would stay the same because it does not distinguish between the explanatory and response variables.

• The correlation would change because changing the units of measurement changes the correlation.

• The correlation would stay the same because changing the units of measurement does not change the correlation.

• The correlation would change because it distinguishes between the explanatory and response variables.

Based on this scatterplot, which point would most likely be considered an outlier?

Ms. Kreppel is interested in the relationship between her students' final exam scores and their scores on a pre-test they took at the beginning of the year. A scatterplot of the data for the 18 students in her class shows linear relationship for these variables. The equation of the least-squares regression line isŷ = 34.2 + 0.60xWhich of the following is a correct interpretation of the slope of this regression model

• For each one-unit increase in final exam score, the model predicts, on average, a 0.60 unit increase in pre-test score.

• The predicted score on the final exam increases by 0.60 points for each increase of 1 point on the pretest.

• About 60% of the variation in exam score that is accounted for by the regression of exam score on pre-test score.

Ms. Kreppel is interested in the relationship between her students' final exam scores and their scores on a pre-test they took at the beginning of the year. A scatterplot of the data for the 18 students in her class shows linear relationship for these variables. The equation of the least-squares regression line is ŷ = 34.2 + 0.60x One student scored a 76 on the pre-test and an 82 on the final exam. Which of the following is that student's residual?

• 2.2

• -7.4

• -2.2

• 7.4

What is a residual?

• making predictions outside of the range of the data

• the percent of the variation in y that is explained by x

• a number that describes the strength of a linear relationship

• the difference between the observed and predicted values

What is the correlation for the following Scatter Plot.

• Weak Positive

• No Correlation

• Strong Negative

• Weak Negative

• Strong Positive

Given the following Scatter Plot, select the option that is most likely the r value.

Given the following Scatter Plot, select the option that is most likely the r value.