Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed actress/actor ages in various years, find the best predicted age of the Best Actor winner given that the age of the Best Actresswinner that year is 32 years. Is the result within 5 years of the actual Best Actor winner, whose age was 36 years?Best ActressBest Actor27 32 30 59 34 33 46 30 60 21 44 51 C36 39 44 53 48 59 53 38 54 43 3544+CFind the equation of the regression line.ŷ=+x(Round the y-intercept to one decimal place as needed. Round the slope to three decimal places as needed.)The best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 32 years is years old.(Round to the nearest whole number as needed.)Is the result within 5 years of the actual Best Actor winner, whose age was 36 years?the predicted age isthe actual winner's age.

Answered: Find the regression equation, letting…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

The datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…
Find the equation of the regression line for the given data. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. What is the regression equation? Predict the value of y for x=503. (Please show me how you figured this out) Predict the value of y for x=641.
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 50 inches. Is the result close to the actual weight of 427 pounds? Use a significance level of 0.05. Chest size (inches) 49 51 53 61 57 45 Weight (pounds) 368 382 420 481 457 287 What is the regression equation? y=enter your response here+enter your response herex (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest size of 50 inches? The best predicted weight for a bear with a chest size of 50 inches is enter your response here pounds. (Round to one decimal place as needed.)
Is It Getting Harder to Win a Hot Dog Eating Contest?Every Fourth of July, Nathan’s Famous in New York City holds a hot dog eating contest. The table below shows the winning number of hot dogs and buns eaten every year from 2002 to 2015, and the data are also available in HotDogs. The figure below shows the scatterplot with the regression line. Year Hot Dogs 2015 62 2014 61 2013 69 2012 68 2011 62 2010 54 2009 68 2008 59 2007 66 2006 54 2005 49 2004 54 2003 45 2002 50 Winning number of hot dogs in the hot dog eating contest Winning number of hot dogs and buns Click here for the dataset associated with this question. (a) Is the trend in the data mostly positive or negative? Positive Negative (b) Using the figure provided, is the residual larger in 2007 or 2008?Choose the answer from the menu in accordance to item (b) of the question statement 20072008 Is the residual positive or…
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place as needed.)
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x Stories, y 762 51 621 46 515 45 508 42 491 39 480 36 (a) x = 502 feet (c) x = 315 feet Find the regression equation. ŷ=x+ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) (b) x = 645 feet (d) x = 731 feet
Find the regression equation, letting the first variable be the predictor (x) variable. Find the best predicted Nobel Laureate rate for a country that has 78.5Internet users per 100 people. How does it compare to the country's actual Nobel Laureate rate of 1.1 per 10 million people? Internet Users Per 100 Nobel Laureates80.3 5.679.6 24.277.3 8.644.6 0.183 6.138.3 0.190.1 25.189.1 7.680.1 8.983.3 12.753.2 1.976.6 12.756.8 3.379.5 1.591.5 11.493.7 25.465.1 3.157.8 1.967.9 1.794.3 31.785.3 31.387.7 1977.7 10.8
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. 483 Height, x Stories, y 772 628 518 508 51 48 45 42 496 37 (a) x=499 feet (c) x=315 feet (b)x=639 feet (d) x = 732 feet 35 Find the regression equation. ŷ=x+ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. O C. OB. O D. OA. Q Q ↓ 0 0 Height (feet) Height (feet) (a) Predict the value of y for x = 499. Choose the correct answer below. OA. 51 OB. 40 60+ 0- 800 60+ 0- 800 Q A 60- → 0 Height (feet) 800 60- 0- 800 0 Height (feet)
Find the regression equation, letting the first variable be the predictor (x) variable. Find the best predicted Nobel Laureate rate for a country that has 79.4 Internet users per 100 people. How does it compare to the country's actual Nobel Laureate rate of 1.2 per 10 million people? Internet Users Per 100 Nobel Laureates 79.3 5.6 80.5 24.2 78.8 8.7 45.2 0.1 82.5 6.2 38 0.1 90.3 25.4 88.6 7.6 80.3 9.1 83.1 12.6 53.3 1.9 76.3 12.7 56.6 3.3 78.5 1.5 91.6 11.5 93.4 25.2 65.3 3.1 57.3 1.9 68.2 1.7 94.8 31.6 85.4 31.3 86.4 19.1 78.3 10.9 2) Check Image
4
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. (a) x 503 feet (c) x = 318 feet (b) x = 649 feet (d) x = 724 feet 766 494 484 520 44 620 508 Height, x Stories, y 51 46 43 39 38 (c) Predict the value of y for x=318. Choose the correct answer below. O A. 34 B. 50 O C. 47 O D. not meaningful (d) Predict the value of y for x=724. Choose the correct answer below. O A. 34 O B. 41 50
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 63 inches. Is the result close to the actual weight of 532 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) 58 414 50 312 65 59 59 499 48 g 450 456 260 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y = x (Round to one decimal place as needed.) - Critical Values of the Pearson Correlation Coefficient r Critical Values of the Pearson Correlation Coefficient r α = 0.05 α=0.01 NOTE: To test Ho: p=0 4 0.950 0.990 against H₁: p0, reject Ho 5 0.878 0.959 if the absolute value of ris 6 0.811 0.917 7 0.754 0.875 greater than the critical value in the table. 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 13 0.553 0.684 14 0.532 0.661 15 0.514 0.641 16 0.497 0.623 17…

Recommended textbooks for you

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

Elementary Statistics: Picturing the World (7th E…

Statistics

ISBN:

9780134683416

Author:

Ron Larson, Betsy Farber

Publisher:

PEARSON

The Basic Practice of Statistics

Statistics

ISBN:

9781319042578

Author:

David S. Moore, William I. Notz, Michael A. Fligner

Publisher:

W. H. Freeman

Introduction to the Practice of Statistics

Statistics

ISBN:

9781319013387

Author:

David S. Moore, George P. McCabe, Bruce A. Craig

Publisher:

W. H. Freeman

SEE MORE TEXTBOOKS