Chapter 3: Q.3.2 (page 176)
Interpret the value of this subject’s residual in context.
Short Answer
Residual = Observed - Predicted.
Chapter 3: Q.3.2 (page 176)
Interpret the value of this subject’s residual in context.
Residual = Observed - Predicted.
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Get started for freeWhat’s my grade? In Professor Friedman’s economics course, the correlation between the students’ total scores prior to the final examination and their final-examination scores is The pre-exam totals for all students in the course have mean and standard deviation The
final-exam scores have mean and standard deviation Professor Friedman has lost Julie’s final exam but knows that her total before the exam was He decides to predict her final-exam score from her pre-exam total.
(a) Find the equation for the appropriate least-squares regression line for Professor Friedman’s prediction. Interpret the slope of this line in context.
(b) Use the regression line to predict Julie’s final exam score.
(c) Julie doesn’t think this method accurately predicts how well she did on the final exam. Determine Use this result to argue that her actual score could have been much higher (or much lower) than the predicted value.
Oil and residuals Refer to Exercise . The following figure shows a residual plot for the least-squares regression line. Discuss what the residual plot tells
To determine the least-squares regression line:
The British government conducts regular surveys of household spending. The average weekly household spending (in pounds) on tobacco products and alcoholic beverages for each of regions in Great Britain was re- corded. A scatterplot of spending on alcohol versus spending on tobacco is shown below. Which of the following statements is true?
(a) The observation is an outlier.
(b) There is clear evidence of a negative association between spending on alcohol and tobacco.
(c) The equation of the least-squares line for this plot would be approximately
(d) The correlation for these data is
(e) The observation in the lower-right corner of the plot is influential for the least-squares line.
Measurements on young children in Mumbai, India, found this least-squares line for predicting height from the arm span x Measurements are in centimeters (cm).
One child in the Mumbai study had a height of and an arm spanThis child’s residual is
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