Chapter 12: Problem 3
Give the equation and graph for a line with \(y\) -intercept equal to 3 and slope equal to -1.
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Chapter 12: Problem 3
Give the equation and graph for a line with \(y\) -intercept equal to 3 and slope equal to -1.
These are the key concepts you need to understand to accurately answer the question.
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The demand for healthy foods that are low in fat and calories has resulted in a large number of "low-fat" or "fat-free" products. The table shows the number of calories and the amount of sodium (in milligrams) per slice for five different brands of fat-free American cheese. $$ \begin{array}{lcc} \text { Brand } & \text { Sodium (mg) } & \text { Calories } \\ \hline \text { Kraft Fat Free Singles } & 300 & 30 \\ \text { Ralphs Fat Free Singles } & 300 & 30 \\ \text { Borden }^{\text {( }} \text { Fat Free } & 320 & 30 \\ \text { Healthy Choice }^{@} \text { Fat Free } & 290 & 30 \\ \text { Smart Beat }^{@} \text { American } & 180 & 25 \end{array} $$ a. Should you use the methods of linear regression analysis or correlation analysis to analyze the data? Explain. b. Analyze the data to determine the nature of the relationship between sodium and calories in fat-free American cheese. Use any statistical tests that are appropriate.
In Exercise we described an informal experiment conducted at McNair Academic High School in Jersey City, New Jersey. Two freshman algebra classes were studied, one of which used laptop computers at school and at home, while the other class did not. In each class, students were given a survey at the beginning and end of the semester, measuring his or her technological level. The scores were recorded for the end of semester survey \((x)\) and the final examination \((y)\) for the laptop group. \({ }^{6}\) The data and the MINITAB printout are shown here. $$ \begin{array}{crr|ccc} & & \text { Final } & & & \text { Final } \\ \text { Student } & \text { Posttest } & \text { Exam } & \text { Student } & \text { Posttest } & \text { Exam } \\ \hline 1 & 100 & 98 & 11 & 88 & 84 \\ 2 & 96 & 97 & 12 & 92 & 93 \\ 3 & 88 & 88 & 13 & 68 & 57 \\ 4 & 100 & 100 & 14 & 84 & 84 \\ 5 & 100 & 100 & 15 & 84 & 81 \\ 6 & 96 & 78 & 16 & 88 & 83 \\ 7 & 80 & 68 & 17 & 72 & 84 \\ 8 & 68 & 47 & 18 & 88 & 93 \\ 9 & 92 & 90 & 19 & 72 & 57 \\ 10 & 96 & 94 & 20 & 88 & 83 \end{array} $$ a. Construct a scatterplot for the data. Does the assumption of linearity appear to be reasonable? b. What is the equation of the regression line used for predicting final exam score as a function of the posttest score? c. Do the data present sufficient evidence to indicate that final exam score is linearly related to the posttest score? Use \(\alpha=.01\) d. Find a \(99 \%\) confidence interval for the slope of the regression line.
Leonardo da Vinci (1452-1519) drew a sketch of a man, }\end{array}\( indicating that a person's armspan (measuring across the back with your arms outstretched to make a "T") is roughly equal to the person's height. To test this claim, we measured eight people with the following results: $$ \begin{array}{l|clll} \text { Person } & 1 & 2 & 3 & 4 \\ \hline \text { Armspan (inches) } & 68 & 62.25 & 65 & 69.5 \\ \text { Height (inches) } & 69 & 62 & 65 & 70 \\ \text { Person } & 5 & 6 & 7 & 8 \\ \hline \text { Armspan (inches) } & 68 & 69 & 62 & 60.25 \\ \text { Height (inches) } & 67 & 67 & 63 & 62 \end{array} $$ a. Draw a scatterplot for armspan and height. Use the same scale on both the horizontal and vertical axes. Describe the relationship between the two variables. b. If da Vinci is correct, and a person's armspan is roughly the same as the person's height, what should the slope of the regression line be? c. Calculate the regression line for predicting height based on a person's armspan. Does the value of the slope \)b$ confirm your conclusions in part b? d. If a person has an armspan of 62 inches, what would you predict the person's height to be?
Why is it that one person may tend to gain weight, even if he eats no more and exercises no less than a slim friend? Recent studies suggest that the factors that control metabolism may depend on your genetic makeup. One study involved 11 pairs of identical twins fed about 1000 calories per day more than needed to maintain initial weight. Activities were kept constant, and exercise was minimal. At the end of 100 days, the changes in body weight (in kilograms) were recorded for the 22 twins. \({ }^{16}\) Is there a significant positive correlation between the changes in body weight for the twins? Can you conclude that this similarity is caused by genetic similarities? Explain. $$ \begin{array}{rrr} \text { Pair } & \text { Twin A } & \text { Twin B } \\ \hline 1 & 4.2 & 7.3 \\ 2 & 5.5 & 6.5 \\ 3 & 7.1 & 5.7 \\ 4 & 7.0 & 7.2 \\ 5 & 7.8 & 7.9 \\ 6 & 8.2 & 6.4 \\ 7 & 8.2 & 6.5 \\ 8 & 9.1 & 8.2 \\ 9 & 11.5 & 6.0 \\ 10 & 11.2 & 13.7 \\ 11 & 13.0 & 11.0 \end{array} $$
How is the cost of a plane flight related to the length of the trip? The table shows the average round-trip coach airfare paid by customers of American Airlines on each of 18 heavily traveled U.S. air routes. $$ \begin{array}{lrr} & \text { Distance } & \\ \text { Route } & \text { (miles) } & \text { Cost } \\ \hline \text { Dallas-Austin } & 178 & \$ 125 \\ \text { Houston-Dallas } & 232 & 123 \\ \text { Chicago-Detroit } & 238 & 148 \\ \text { Chicago-St. Louis } & 262 & 136 \\ \text { Chicago-Cleveland } & 301 & 129 \\ \text { Chicago-Atlanta } & 593 & 162 \\ \text { New York-Miami } & 1092 & 224 \\ \text { New York-San Juan } & 1608 & 264 \\ \text { New York-Chicago } & 714 & 287 \\ \text { Chicago-Denver } & 901 & 256 \\ \text { Dallas-Salt Lake } & 1005 & 365 \\ \text { New York-Dallas } & 1374 & 459 \\ \text { Chicago-Seattle } & 1736 & 424 \\ \text { Los Angeles-Chicago } & 1757 & 361 \\ \text { Los Angeles-Atlanta } & 1946 & 309 \\ \text { New York-Los Angeles } & 2463 & 444 \\ \text { Los Angeles-Honolulu } & 2556 & 323 \\ \text { New York-San Francisco } & 2574 & 513 \end{array} $$ a. If you want to estimate the cost of a flight based on the distance traveled, which variable is the response variable and which is the independent predictor variable? b. Assume that there is a linear relationship between cost and distance. Calculate the least-squares regression line describing cost as a linear function of distance. c. Plot the data points and the regression line. Does it appear that the line fits the data? d. Use the appropriate statistical tests and measures to explain the usefulness of the regression model for predicting cost.
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