The data set for a random sample of 10 soccer player's heights compared to their shoe sizes is summarized in the table.Shoe Size (U.S.) Height (inches)7.58128.5910.51112.51310.56370.5727169.57075647268Part A: What is the equation of the least-squares regression line?Part B: If a soccer player wears a size 10 and is 68 inches tall, what is their residual? Show all mathematical work.Part C: Interpret the meaning of the residual from part B. (

Answered: The data set for a random sample of 10…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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A blood pressure measurement consists of two numbers: the systolic pressure, which is the maximum pressure taken when the heart is contracting, and the diastolic pressure, which is the minimum pressure taken at the beginning of the heartbeat. Blood pressures were measured, in millimeters, for a sample of 8 adults. The following table presents the results. Systolic Diastolic 124 84 106 84 102 77 113 77 118 66 117 87 130 74 115 70 The least-squares regression line y=b0+b1x=89.5234-0.1051x and Σ(x-x bar) squared =569.8750 are known for this data. Use the P-value method to test H0:β1=0 versus H1:β1<0. Can you conclude that systolic blood pressure is useful in predicting diastolic blood pressure? Use the α=0.10 level of significance and the TI-84 calculator. Compute the test statistic. Always round t-score values to three decimals places.
A pediatrician wants to determine the relation that exists between a child's height, x, and head circumference, y. She randomly selects 11 children from her practice, measures their heights and head circumferences, and obtains the accompanying data. Complete parts (a) through (g) below. Click the icon to view the children's data. Data table (a) Find the least-squares regression line treating height y =x+ (O (Round the slope to three decimal places and round the d Height (inches), x Head Circumference (inches), y O. 28 17.6 24.5 17.1 25.75 17.1 25.75 17.5 24.25 17.0 27.75 17.7 26.5 17.3 27.25 17.6 26.5 17.3 26.5 17.5 27.75 17.6 Print Done Help me solve this View an example Get more help - Media - Clear all Check answer
A researcher records data on 7 adult pairs' heights (in inches) to compare the physical characteristics of brothers and sisters. Brother Sister 71 69 68 64 6 65 67 63 70 65 71 62 66 62 Mean 68.4285 64.2857 SD 2.2253 2.4299 r=0.4050 What would the least-squares regression equation be for predicting the brother's height from the sister's? A. brother's height = 0.037+44.58 * sister's height B. brother's height = 44.58 + 0.371* sister's height C. brother's height = 20.71 + 0.029 * sister's height D. brother's height = 3.28- 40.68 * sister's height If the sister's height is the same as the mean (64.2857 inches), what would the brother's predicted height be A. 68.4285 (the same as the mean as well) B. 62.1234 C. 70.8990 D. None of the above. Which of the following would be correct? A. The pair of means, (68.4285, 64.2857), lies on the linear regression line. B. The effectiveness of the linear regression model is about 16%, C. The effectiveness of the linear regression model is 10096. D. Both…
The following is a table showing the price of car insurance based on how much driving experience that an insurance holder has. Use the years of driving experience as your explanatory (independent) variable and the monthly insurance premium as your response (dependent) variable. Years of driving experience 0 1 2 3 4 5 6 7 8 Cost of monthly insurance premium 67 63 62 59 50 42 39 34 32 a) What is the least squares regression line for this bivariate dataset? (write in y=mx+b form) b) What is the correlation coefficient? c) Find the residual cost of someone with 5 years of driving experience (difference between predicted and observed values) d) Interpret the y-intercept and slope of the regression line in context of the problem.
The table below shows the heights (inches) and weights (pounds) of 9 randomly selected children. Child Data Height (inches), x 36 56 58 59 61 63 65 69 73 Weight (pounds), y 69 89 96 74 110 90 123 110 128 (a) Construct a scatter diagram for the data, where the weight of the child is the response variable. (b) Determine the least-squares regression line for the data and graph the line on the scatter diagram from part (a). (use calculator) (show what did you do on the calculator) (c) Interpret the slope and the y–intercept in the context of the problem. (d) Predict the weight of a child that is 57 inches tall. Comparing with the observed value, what is the residual? Is the observed weight above or below average? (e) Determine the correlation coefficient, r. Is there a correlation? Discuss the strength of the correlation and why. (f) Are heights and weights of children linearly related? Why or why not? Be sure to justify your answer by using the appropriate method. (g)…
Name Her Age His Age Barack and Michelle Obama 45 47 George W. and Laura Bush 54 54 Bill and Hillary Clinton 45 46 Ronald and Nancy Reagan 55 64 Gerald and Betty Ford 59 69 Lyndon and Lady Bird Johnson 56 61 John and Jacqueline Kennedy 31 43 Dwight and Mamie Eisenhower 50 55 (c) Remove the outlier and compute the least-squares regression line for predicting the president's age from first lady's age. Round the slope and y -intercept values to at least four decimal places. Regression line equation: =y
50
Suppose John is a high school statistics teacher who believes that watching many hours of TV leads to lower test scores. Immediately after giving the most recent test, he surveyed each of the 24 students in his class and asked them how many hours of TV they watched that week. He then matched each student's test grade with his or her survey response. After compiling the data, he used hours of TV watched to predict each student's test score. He found the least-squares regression line to be ?̂ =−1.5?+85y^=−1.5x+85. He also calculated that the value of ?r, the correlation coefficient, was −0.61. Which of the choices identifies the correct value of the coefficient of determination, ?2R2, and gives a correct interpretation of its meaning?
This table shows the average heights for American boys in 1990. Age (years) Height (cm) birth 50.8 2 83.8 3 91.4 5 106.6 7 119.3 10 137.1 14 157.5 Decide which variable should be the independent variable and which should be the dependent variable. Draw a scatter plot of the data. Does it appear from inspection that there is a relationship between the variables? Why or why not? Calculate the least-squares line. Put the equation in the form of: ŷ = a + bx Find the correlation coefficient. Is it significant? Find the estimated average height for a one-year-old. Find the estimated average height for an eleven-year-old. Does it appear that a line is the best way to fit the data? Why or why not? Are there any outliers in the data? Use the least squares line to estimate the average height for a sixty-two-year-old man. Do you think that youranswer is reasonable? Why or why not? 10. What is the slope of the least-squares (best-fit) line?…

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