(c) Use the regression equation to predict the head circumference of a child who is 24.5 inches tall. Data TableHeight (inches), x Head Circumference (inches), y27.517.524.7517.125.752624.527.7526.7527.2526.526.527.7517.217.616.917.617.317.517.317.517.5 A pediatrician wants to determine the relation that exists between a child's height, x, and head circumference, y. She randomly selects 11 children from her practice, measures theirheights and head circumferences, and obtains the accompanying data. Complete parts (a) through (g) below.Click the icon to view the children's data.Interpret the y-intercept, if appropriate. Select the correct choice below and, if necessary, fill in the answer box to complete your choice.in., on average.O A. For every inch increase in height, the head circumference increases by(Round to one decimal place as needed.)OB. For a height of 0 inches, the head circumference is predicted to be(Round to one decimal place as needed.)in.C. For every inch increase in head circumference, the height increases by(Round to one decimal place as needed.)y =in.(Round to two decimal places as needed.)COD. For a head circumference of 0 inches, the height is predicted to be(Round to one decimal place as needed.)E. It is not appropriate to interpret the y-intercept.(c) Use the regression equation to predict the head circumference of a child who is 24.5 inches tall.in.in., on average.

first we have to find regression equation.

Answered: (c) Use the regression equation to…

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

You are studying how a penguin's flipper length (in mm) explains its body mass (in grams) using linear regression. You choose a non-directional alternative to be safe. You calculate an R2=0.7621. What is the interpretation of this value? O76.21% of the variability in body mass is explained by the flipper length. O 76.21% of the variability in flipper length is explained by the body mass. 0 Flipper length and body mass have a positive relationship becase R² is positive O76.21% of the body mass values will be inside the confidence interval
A doctor wanted to determine whether there is a relation between a male’s age and his HDL (so-called good cholesterol). He randomly selected 9 of his patients and determined their HDL cholesterol. The data is reported in the table below: a) Compute the regression equation for HDL as a function of age. b)Interpret the meaning of the regression parameters.
Use the regression line to make the appropriate prediction. A random sample of records of electricity usage of homes in the month of July gives the amount of electricity used and size (in square feet) of 135 homes. A regression was done to predict the amount of eleçtricity used (in kilowatt-hours) (y) from size (x). The residuals plot indicated that a inear model is appropriate. The model is y = 0.2x+ 1271. How much electricity would you predict would be used in a house that is 2471 square feet? 494.2 kilowatt-hours O 6000.00 kilowatt-hours O 1765.2 kilowatt-hours O 776.8 kilowatt-hours 3742.2 kilowatt-hours
10:56 AA www-awn.aleks.com O REGRESSION AND CORRELATION Predictions from the least-squares regressio. OC OO D The managers of an electric utility wish to examine the relationship between temperature and electricity use in the utility's service region during the summer months. In particular, the managers wish to be able to predict total electricity use for a day from the maximum temperature that day. The bivariate data below give the maximum temperature (in degrees Fahrenheit) and the electricity use (in thousands of kilowatt hours) of electricity generated and sold for a random sample of sixteen summer days. A best-fitting line for the data, obtained from least- squares regression, is given by =53.28 + 3.07.x, in which x denotes the maximum temperature and y denotes the electricity use. This line is shown in the Figure 1 scatter plot. Temperature, x Electricity use, y (in degrees Fahrenheit) (in thousands of kilowatt hours) 78.4 295.4 72.5 232.1 00- 72.7 276.8 94.5 363.4 375 94.8 335.6…
The regression line for a data set showing the monthly utility bill U in a certain city versus the square footage F of the residence is given by U = 0.2F − 100 dollars. What monthly utility bill would be expected for a 2500 square foot home in this city? $
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-1.375 b=26.852 r2=0.395641 r=-0.629 Use this to predict the number of situps a person who watches 14 hours of TV can do (to one decimal place)
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (xx) and number of sit ups a person can do (yy). The results of the regression were: y=ax+b a=-1.223 b=22.907 r2=0.600625 r=-0.775 Use this to predict the number of sit ups a person who watches 5 hours of TV can do, and please round your answer to a whole number.
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: ý = bo + bịx bo = 36.465 - 1.082 b1 - 0.646 Use this to predict the number of situps a person who watches 2.5 hours of TV can do (to one decimal place)
Draw the regression line for the following equation: Y = -3 + (1) X Show your calculation for a low and high value on the predictor value.
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.96 b=35.944 r2=0.736164 r=-0.858 Use this to predict the number of situps a person who watches 10.5 hours of TV can do (to one decimal place)
In rolling 2 fair dice, find the probability: P(sum39| sum>8)
Use the regression equation, Ŷ = 3X + 4, to find the predicted Y value corresponding to X = 2 The predicted Y value = ?

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

​(c) Use the regression equation to predict the head circumference of a child who is 24.5 inches tall.

(c) Use the regression equation to predict the head circumference of a child who is 24.5 inches tall.