**Kelly's Exercise and Weight Loss Analysis**The table below shows Kelly's hours of exercise and her corresponding weight loss each week:| Hours of exercise | Weight loss (pounds) ||-------------------|----------------------|| 1.3 | 0.5 || 3 | 2.8 || 5 | 3.5 || 2 | 2.5 || 4 | 3 |---**Questions:**(a) Use a linear regression model to estimate how many hours Kelly will have to exercise a week in order to lose 4.2 pounds.- **Estimated Hours:** (Round your answer to one decimal place. Do not write the units.)(b) According to the coefficient of determination, what percentage of the variation in weight loss is unexplained and due to other factors?- **Unexplained Variation:** (Round your answer to one decimal place. Do not write the % sign. For example, do not write 0.1 as .1.)---**Instruction for Calculation:**1. **Linear Regression Model:** A statistical method for modeling the relationship between a dependent variable and one or more independent variables. In this case, the dependent variable is weight loss, and the independent variable is hours of exercise.2. **Coefficient of Determination (R²):** A measure that explains how much of the variation in the dependent variable can be predicted from the independent variable(s).**Note:** Use statistical software or a calculator capable of performing linear regression analysis for these computations.

Answered: Image /qna-images/answer/34ed0104-88ed-4ae4-b280-749f1ede5de3.jpg

Answered: The table shows Kelly's hours of…

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

What is the dollar amount of change in sales for each new year according to the regression (slope) model? Do not use commas or $ in your answer.
An experiment is run. The mass of an object is recorded over time. Time (min) Mass (g) 32 40 36 32 37 32 39 30 50 27 Using your calculator, run a linear regression to determine the equation of the line of best fit. Round to two decimal places, use x for the variable.y=Using your equation, estimate the mass of the object at 41 minutes.grams=
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.)
A corporation has asked you to prepare some multiple regression equations to estimate the effect of variables on fuel economy. The data for this study are shown below, and the dependent variable is miles per gallon. Complete parts a and b. Miles 43.3 Horsepower 50 Weight 1985 36.3 67 1885 32.7 51 1990 + ŷ =) ()×₁ + ( )×₂ (Round to four decimal places as needed.) 39.5 72 2090 36 62 1880 19.2 110 3370 19.1 142 3775 20.9 136 3560 19.9 101 3165 a. Prepare a regression equation that uses vehicle horsepower and vehicle weight as independent variables. Let x₁ be defined as horsepower and x₂ be defined as weight. 20.8 94 2720
Statistical technique used to determine the degree to which two variables are related is known as a. Regression b. Correlation c. None of these d. Dispersion
Bookstore sales revisited Recall the data we saw inChapter 6, Exercise 3 for a bookstore. The manager wantsto predict Sales from Number of Sales People Working. Number of SalesPeople Working Sales (in $1000)2 103 117 139 1410 1810 2012 2015 2216 2220 26 Dependent variable is SalesR-squared = 93.2,s = 1.477 Variable CoefficientIntercept 8.1006Num_Workers 0.9134 a) Write the regression equation. Define the variablesused in your equation.b) What does the slope mean in this context?c) What does the y-intercept mean in this context? Is itmeaningful?d) If 18 people are working, what Sales do you predict?e) If sales for the 18 people are actually $25,000, what isthe value of the residual?f) Have we overestimated or underestimated the sales?
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x 150 180 130 120 90 190 (a) x=160 calories (b) x=100 calories Sodium, y 430 480 320 360 290 550 (c) x=140 calories (d) x=50 calories Find the regression equation. y=nothingx+(nothing) (Round to three decimal places as needed.) Choose the correct graph below. A. 02000560CaloriesSodium (mg) A scatterplot has a horizontal axis labeled "Calories" from 0 to 200 in increments of 20 and a vertical axis labeled "Sodium (in milligrams)" from 0 to 560 in increments of…
Roller coasters get their speed as a result of dropping down a steep incline. The table below gives height of a drop and the speed achieved for different roller coasters around the world. Drop in Meters (m 25 30 28 58 55 40 90 100 Speed of the coaster (k.p.h) 80 90 78 93 90 93 105 128 Have your calculator find the linear regression for the roller coaster data above. Write the linear model, clearly define the variables and state correlation coefficient and clearly interpret the slope. Use the model to find the drop height that will result in a coaster speed of 150 kph. Have your calculator find the exponential regression for this data. Write the exponential model, clearly define the variables and state correlation coefficient. Use the model to find the drop height that will result in a…
Using data from 50 workers, a researcher estimates Wage Be + B₁Education + B2Experience + B3Age +, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. A portion of the regression results is shown in the following table. Coefficients Standard Error t Stat p-Value Intercept 7.45 3.79 1.97 0.0554 Education 1.06 0.37 2.86 0.0063 Experience 0.37 0.18 2.06 0.0455 Age -0.02 0.06 -0.33 0.7404 a-1. Interpret the point estimate for ẞ1. As Education increases by 1 year, Wage is predicted to increase by 1.06/hour. As Education increases by 1 year, Wage is predicted to increase by 0.37/hour. As Education increases by 1 year, Wage is predicted to increase by 1.06/hour, holding Age and Experience constant. As Education increases by 1 year, Wage is predicted to increase by 0.37/hour, holding Age and Experience constant. a-2. Interpret the point estimate for ẞ2. ○ As Experience…
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x 150 180 120 130 90 190 P (a)x= 170 calories (c) x 140 calories (b)x= 100 calories (d) x = 210 calories Sodium, y 430 480 350 370 290 530 REED Find the regression equation. ŷ=x+0) (Round to three decimal places as needed.) 4
statistic please answer
PVan

SEE MORE QUESTIONS

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