Problem 5 Using a Regression Equation The regression equation for the association between BMI and total cholesterol level is y 28.07 6.49x A. Suppose a participant has a BMI of 26. What would we estimate the total cholesterol to be? B. Suppose two individuals have a BMI that differs by 3 units. What is the estimated difference in total cholesterol? 18-35 C. What ranges of BMI should the equation be used to predict total cholesterol?

Problem 5 Using a Regression Equation The regression equation for the association between BMI and total cholesterol level is y 28.07 6.49x A. Suppose a participant has a BMI of 26. What would we estimate the total cholesterol to be? B. Suppose two individuals have a BMI that differs by 3 units. What is the estimated difference in total cholesterol? 18-35 C. What ranges of BMI should the equation be used to predict total cholesterol?

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Description: Problem 5 Problem 5 Using a Regression EquationThe regression equation for the association betweenBMI and total cholesterol level isy 28.07 6.49xA. Suppose a participant has a BMI of 26. What wouldwe estimate the total cholesterol to be?B. Suppose tw

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter5: A Survey Of Other Common Functions

Section5.6: Higher-degree Polynomials And Rational Functions

Problem 1TU: The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t=...

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Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.
Question #9 Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 400metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports 233 269 364 492 548 Crash Fatality Rate 15.9 15.7 15.4 15.4 15 Find the equation of the regression line. y= ___________+( __________ ) x (Round the y-intercept to three decimal places as needed. Round the slope to four decimal places as needed.) The best predicted crash fatality rate for a year in which there are 400 metric tons of lemon imports is _________fatalities per 100,000 population. (Round to one decimal place as needed.) Is the prediction worthwhile? A. Since all of the requirements for finding the equation of the regression line are…
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QUESTION 16 A set of n = 20 pairs of X and Y scores has SS X = 10, SS Y = 40, and SP = 30. What is the slope for the regression equation for predicting Y from X? a. b = 0.25 b. b = 3.33 c. b = 4.00 d. b = 0.33
Consider the following scenario for Questions 6 through 9: The City of Bellmore’s police chief believes that maintenance costs on high-mileage police vehicles are much higher than those costs for low-mileage vehicles. If high-mileage vehicles are costing too much, it may be more economical to purchase more vehicles. An analyst in the department regresses yearly maintenance costs (Y) for a sample of 200 police vehicles on each vehicle’s total mileage for the year (X). The regression equation finds: Y = $50 + .030X with a r2 of .90 What is the IV? What is the DV? If the mileage increases by one mile, what is the predicted increase in maintenance costs? If a vehicle’s mileage for the year is 50,000, what is its predicted maintenance costs? What does an r2 of .90 tell us? Is this a strong or weak correlation? How can you tell?
Question 4 The following table displays the mathematics test scores for a random sample of college students, along with their final SY16C grades. Fit the regression line y = a+bx to the data and interpret the results. Use the regression equation to determine the SY16C grade for a college student who scored 60 on their achievement test. What would their SY16C grade be? Mathematics test (x) SY16C grades (y) 1 39 65 2 43 78 3 21 52 4 64 82 5 57 92 6 47 89 7 28 73 8 75 98 9 34 56
Question 1 The National Highway Association is studying the relationship between the number of bidders on a highway project and the winning (lowest) bid for the project. Of particular interest is whether the number of bidders increases or decreases the amount of the winning bid. d. Determine the regression equation. e. Do more bidders tend to decrease the amount of the winning bid? Use the 0.05 significance level. f. Estimate the amount of the winning bid if there were eight bidders. Note: 1. please clear answer no Whois one d,e,&f 2. No need excel formula
Question 18 At a local club, the ages of the members and the times they took to run a 10 km race arerecorded. For a random sample of 25 club members aged between 27 and 60, their ages(x years) and times (y minutes) produce the following regression line. y = 0.83x + 41.28Four new members join the club. Their respective ages (in years) are 26, 18, 22, and 28. When therespective race times for the 4 new members are estimated, which one of these estimated race timesis the most reliable?A. 62.86 minutesB. 56.22 minutesC. 59.54 minutesD. 64.52 minutes Question 19 The data of the number of ‘centuries’ i.e. a scores of 100 runs or more, scored by players at acricket club during a season are given in the following table.Number of centuries Number of players0 41 k2 33 24 38 1Given that the mean number of centuries scored per player is 1.95, find the value of k.A. 7B. 3C. 4D. 1 Question 20The asking prices (in Rands) and the actual selling prices (in Rands), after bargaining, of 8commodities are…
Suppose that in a certain neighborhood, the cost of a home is proportional to the size of the home in square feet. If the regression equation quantifying this relationship is found to be (cost) = 94.872*(size) + 612.216, what does the slope indicate? Question 21 options: 1) When cost increases by 1 dollar, size increases by 94.872 square feet. 2) We are not given the dataset, so we cannot make an interpretation. 3) When size increases by 1 square foot, cost increases by 612.216 dollars. 4) When cost increases by 1 dollar, size increases by 612.216 square feet. 5) When size increases by 1 square foot, cost increases by 94.872 dollars.
Use the dataset in Table 2 to answer the questions. The table shows the ages (in years) of seven children and the number of words in their vocabulary. For problems 9-12, use the regression equation found in question 7 to predict the value of for the values of given in each question unless it is not meaningful. If it is not meaningful to predict the value of for the -value, explain why not. Table 2. Vocabulary Age Vocabulary 3 1100 4 1300 4 1500 5 2100 6 2600 2 460 3 1200 7. What is the equation of the regression line? 8. Construct a scatter plot for the data showing the regression line on the same graph. For problems 9-12, see the instructions above. 9. x=2years 10. x=3years 11. x=6years 12. x=12years