Chapter 3 Review - Statistics

For children between the ages of 18 months and 29 months, there is approximately a linear relationship between height and age. The relationship can be represented by = 64.93 + 0.63x, where y represents height (in centimeters) and x represents age (in months). What does the slope mean in context of the problem?

• Babies grow 0.63 cm every month

• On average, babies grow 0.63 cm every month

• On average, babies grow 64.93 cm every month

• On average, a baby grows one inch every 0.63 month

For children between the ages of 18 months and 29 months, there is approximately a linear relationship between height and age. The relationship can be represented by = 64.93 + 0.63x, where y represents height (in centimeters) and x represents age (in months). Joseph is 22.5 months old and is 80 centimeters tall. What is Josephs residual?

• 79.105

• 80

• .895

• -.895

Mr. Nerdly asked the students in his AP Statistics class to report their overall grade point averages and their SAT Math scores. The scatterplot below provides information about his students’ data. The dark line is the least-squares regression line for the data, and its equation is y = 270.45 + 109.42x . Explain the meaning of the slope in context of the problem.

• On average, for each GPA point students score on their SAT Math rises 109.42 points

• On average, students SAT Math score rises 270.45 points for every GPA point

• On average, for every point on the SAT Math score students GPA rises 109.42 points

• On Average, for every point on the SAT Math score students GPA rises 270.45 points

Mr. Nerdly asked the students in his AP Statistics class to report their overall grade point averages and their SAT Math scores. The scatterplot below provides information about his students’ data. The dark line is the least-squares regression line for the data, and its equation is y = 270.45 + 109.42x . The highlighted dot shows a point for one of the students. What is their predicted score on the SAT Math.

• 587.768

• 670

• 2.9

• 73581.85

Mr. Nerdly asked the students in his AP Statistics class to report their overall grade point averages and their SAT Math scores. The scatterplot below provides information about his students’ data. The dark line is the least-squares regression line for the data, and its equation is y = 270.45 + 109.42x . The highlighted dot shows a point for one of the students. What is their residual?

• 587.768

• 670

• -82.232

• 82.232

Mr. Nerdly asked the students in his AP Statistics class to report their overall grade point averages and their SAT Math scores. The scatterplot below provides information about his students’ data. The dark line is the least-squares regression line for the data, and its equation is y = 270.45 + 109.42x . The highlighted dot shows a point for one of the students. What effect would removing this point have on the correlation coefficient?

• No effect

• Make it stronger

• Make it weaker

• Make it zero

Mr. Nerdly asked the students in his AP Statistics class to report their overall grade point averages and their SAT Math scores. The scatterplot below provides information about his students’ data. The dark line is the least-squares regression line for the data, and its equation is y = 270.45 + 109.42x . The highlighted dot shows a point for one of the students. What effect would removing this point have on the LSRL?

• Decrease the y-intercept and increase the slope

• No effect

• Increase the y-intercept and decrease the slope

• Increase the y-intercept and increase the slope

A copy machine dealer has data on the number x of copy machines at each of 89 customer locations and the number y of service calls in a month at each location. Summary calculations give mean (x) = 8.4, Sx= 2.1, mean of y = 14.2, Sy = 3.8, and r = 0.86. Calculate the LSRL.

• y = 1.09 + 1.56x

• y = 1.56 + 1.09x

• y = 1.17 + .48x

• y = .48 + 1.01x

In a statistics course, a linear regression equation was computed to predict the final-exam score from the score on the first test. The equation was y = 10 + 0.9x where y is the final-exam score and x is the score on the first test. Stan scored 93 on the first test. What is the predicted value of Stan scored a 98 on the final exam. What is his residual?

• 4.3

• -4.3

• 98.2

• 94

A regression of the amount of calories in a serving of breakfast cereal vs. the amount of fat gave the following results: Calories = 97.1053 + 9.6525(Fat). Explain the meaning of the slope in context of the problem.

• On average, for each calorie the amount of fat increase 9.6525 grams

• On average, for each calorie the amount of fat increases 97.1053 grams

• On average, for each gram of fat calories increase by 9.6525

• On average, for each gram of fat calories increase by 97.1053