4. An observational study was conducted to investigate the association between age and total serumcholesterol. The study involved 125 participants with an average age of 44.3 and an age rangebetween 35-55 years. The regression equation was calculated and is as follows:y = 124.4 + 1.6xa) Estimate the total serum cholesterol for a 50-year old person.b) Estimate the total serum cholesterol for a 44-year old person.c) Would it be appropriate to utilize the equation to predict a 70-year old individual's cholesterollevel? Please explain your answer.

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Description: 4. An observational study was conducted to investigate the association between age and total serumcholesterol. The study involved 125 participants with an average age of 44.3 and an age rangebetween 35-55 years. The regression equation was calculate

The total serum cholesterol for a 50-year old person will be:

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a) Estimate the total serum cholesterol for a 50-year old person. b) Estimate the total serum cholesterol for a 44-year old person. c) Would it be appropriate to utilize the equation to predict a 70-year old individual's cholesterol level? Please explain your answer.

a) Estimate the total serum cholesterol for a 50-year old person. b) Estimate the total serum cholesterol for a 44-year old person. c) Would it be appropriate to utilize the equation to predict a 70-year old individual's cholesterol level? Please explain your answer.

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

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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?
A company has a set of data with employee age (X) and the corresponding number of annual on-the-job-accidents (Y). Analysis on the set finds that the regression equation is Y=60-0.5*X. What can be said of the correspondence (relation) between age and accidents? Are younger workers safer or more prone to accident? What is the likely number of accidents for someone aged 25?
1. The following data give the percentage of women working in five companies in the retail and trade industry. The percentage of management jobs held by women in each company is also shown. % Working 69 48 73 54 61 % Management 51 21 61 51 43 Develop the estimated regression equation by computing the values of b0 (y-intercept) and b1 (slope).Predict the percentage of management jobs held by women in a company that has 65% women employees.
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The admissions officer for a certain college developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and high school GPA. ŷ = −1.39 + 0.0234x1 + 0.00482x2 where x1 = high-school grade point average x2 = SAT mathematics score y = final college grade point average. #1)A high-school average 84 corresponds to x1 = 84 and a score of 535 on the SAT mathematics test corresponds to x2 = 535. Substitute these values into the estimated regression equation to find the final college GPA, rounding the result to two decimal places. GPA = −1.39 + 0.0234x1 + 0.00482x2 = -1.39 +0.0234 (_____________) + 0.00482 (535) = __________________
An observational study was conducted to investigate the association between age and total serum cholesterol. The study involved 125 participants with an average age of 44.3 and an age range between 35-55 years. The regression equation was calculated and is as follows: y = 124.4 + 1.6x 1.Estimate the total serum cholesterol for a 50-year old person. 2. Estimate the total serum cholesterol for a 44-year old person. 3. Would it be appropriate to utilize the equation to predict a 70-year old individual’s cholesterol level? Please explain your answer.
It is considered that the number of employees in the enterprise affects the number of production. Data are given below. Which of the following is the simple linear regression equation?
In the simple linear regression equation,the term b1 represents the A)estimated intercept B)explanatory variable C)estimated slope D)estimated or predicted response
Consider the following regression analysis between sales (Y in $1,000) and social media advertising (X in dollars).Ŷ = 55,000 + 7XThe regression equation implies that an ________. Multiple Choice increase of $7 in advertising is associated with an increase of $7,000 in sales increase of $1 in advertising is associated with an increase of $7 in sales increase of $1 in advertising is associated with an increase of $62,000 in sales increase of $1 in advertising is associated with an increase of $7,000 in sales
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The admissions officer for a certain college developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and high school GPA. ŷ = −1.39 + 0.0234x1 + 0.00482x2 where x1 = high-school grade point average x2 = SAT mathematics score y = final college grade point average. (a) Interpret the coefficients in this estimated regression equation. (b) Predict the final college GPA for a student who has a high-school average of 84 and a score of 535 on the SAT mathematics test.
Twenty members of an athletic club are studying the relationship between the time it takes an individual athlete to reach a given level of fatigue during exercise (time to fatigue, measured in minutes) and athletic performance. For each member, time to fatigue and a performance score were recorded. The computer output of the regression analysis is shown in the table. Term CoefCoef SE CoefSE Coef TT Constant 39.88 4.24 9.41 Time to fatigue 3.92 0.71 5.52 Which of the following is a 90 percent confidence interval for the slope of the regression line relating performance score and time to fatigue? Assume that the conditions for inference are met.