Data on 12 randomly selected athletes was obtained concerning their cardiovascular fitness (measured bytime to exhaustion running on a treadmill) and performance in a 20-km ski race. Both variables weremeasured in minutes and a regression analysis was performed.ski 85 2.5. treadmill=Coefficients Estimate(Intercept)Treadmill85- 2.5Std. ErrorWhat is the test statistic?-2.50.451Is there sufficient evidence to conclude that there is a linear relationship between cardiovascular fitnessand ski race performance? Round your answers to three decimal places.Using your answer from the previous question, find the p-value.Part 2 o

The provided information is as follows:The regression equation is given as The least-square…

Answered: Data on 12 randomly selected athletes…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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In a sample of cars reviewed by Motor Trend magazine, the mean horsepower (hp) was 150 hp with a standard deviation of 36 hp. The mean weight (lbs) was 2500 lbs with a standard deviation of 720 lbs. Assume the relationship between weight and horsepower is linear and has a correlation of r = +0.55. What is the slope of the linear regression model predicting weight (y-variable) from horsepower (x-variable)? 9 13 15 11
Write the formula for the estimated regression line and interpret the slope of the estimated regression line, the intercept of the estimated regression line- Is it meaningful?, and the estimated R2. Based on the fitted regression model, what is the predicted ATST for a child who is 7 years old? What is the correlation between AGE and ATST? Does the residual plot suggest that the fitted regression line is inappropriate for these data? Explain why or why not. Suppose that a new subject is added to the study data and that subject is 12.5 years old with an ATST of 580 minutes. If the regression model were to be refit with this additional data point, would the new slope be greater than or less than -14.041? Justify your response.
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A car lot wants to predict the # of car accessories they need to sell monthly based on the number of cars sold. The car lot owner randomly selects 12 months of data. The simple linear regression equation is ý = 14 - 2x. The coefficient of determination is 0.6364. What is the correlation coefficient to describe the relationship between these two variables? Multiple Choice
Data on 11 randomly selected athletes was obtained concerning their cardiovascular fitness (measured by time to exhaustion running on a treadmill) and performance in a 20-km ski race. Both variables were measured in minutes and a regression analysis was performed. Ski 88 2.5 . Treadmill Coefficients Estimate Std. Error 0.41 (Intercept) Treadmill 1.11 88 -2.5 Is there sufficient evidence to conclude that there is a linear relationship between cardiovascular fitness and ski race performance? (a). The test statistic is (b). The p-value is (use four decimal places) (use four decimal places) (c). At the 2% significance level, we Select an answer the null hypothesis and conclude that there is Select an answer evidence to conclude that there is a linear relationship between cardiovascular fitness and ski race performance.
The fish in my pond have mean length 10 inches and mean weight 4 pounds. The correlation coefficient of length and weight is .9. If the length of a particular randomly selected fish is reported to be 10 inches, then what should we predict for the weight of that fish using simple linear regression? 4 10 2.5 NOT ENOUGH INFORMATION GIVEN NONE OF THE OTHERS
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Prev The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age Bone Density 61 62 68 69 40 357 350 343 340 315 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Table Copy Data Next
a ift = The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, bo + b₁x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. tab ** Answer How to enter your answer (opens in new window) Step 2 of 6: Find the estimated y-Intercept. Round your answer to three decimal places. esc 1945 ! 1 q alt a Z ebook x360 ng from any angle. @ 2 W S →>> X # 3 e d C $ 4 C r f Age Bone Density 359 % 5 V t g 36 51 63 66 70 357 328 314 310 Oll A 6 b y hp h & 7 O n u j * 8 N O i m ( 9 k O 100- 4 Tables ctrl { [ Keypad Keyboard Shortcuts Previous step answers Submit Answer D + = 11 : 90 ; ? Copy Data O SEAR Dec 2 Table ] USE YOUR SMARTPHONE FOR…
Use the shoe print lengths and heights shown below to find the regression equation, letting shoe print lengths be the predictor (x) variable. Then find the best predicted height of a male who has a shoe print length of 28.5 cm. Would the result be helpful to police crime scene investigators in trying to describe the male? Use a significance level of α=0.05. Shoe Print (cm) 29.1 29.1 31.8 31.9 27.5 Foot Length (cm) 25.7 25.4 27.9 26.7 25.1 Height (cm) 175.4 177.8 185.2 175.4 173.2 The best predicted height is enter your response here cm. (Round to two decimal places as needed.) Would the result be helpful? A. No, because the description would be the same regardless of shoe print length. B. Yes, because the description would be based on an actual shoe print length. C. Yes, because the correlation is strong, so the predicted…

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