8:35KA pediatrician wants to determine the relation that exists between a child's height, x, and head circumference, y. Sherandomly selects 11 children from her practice, measures their heights and head circumferences, and obtains theaccompanying data. Complete parts (a) through (g) below.Click the icon to view the children's data.(a) Find the least-squares regression line treating height as the explanatory variable and head circumference as theresponse variable.Data Tabley = 0.194 x + (12.5)(Round the slope to three decimal places and round the constant to one decimal place as needed.)(b) Interpret the slope and y-intercept, if appropriate.First interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete yourchoice.Height (inches), x Head Circumference (inches), y D27.7517.824.7517.325.7517.426.2517.72517.128.2517.926.7517.52717.717.517.717.8262627.5(Round toPrinttwo decimal places as needed.)|||LTE 2.1 4G=DoneOXaverage.(c) Use the regression equation to predict the head circumference of a child who is 25 inches tall.y = 0.194 in.., on average.41%fill in the answer box toaverage.average.

(a) Obtain the regression equation. The regression equation is obtained below as follows: From the…

Answered: 8:35 K A pediatrician wants 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

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KidsFeet Regression Line y-Intercept The KidsFeet dataframe contains data collected on 39 fourth grade students in Ann Arbor, MI, in October 1997. Two of the measurements taken on the children were the length in centimeters, (length), and width in centimeters, (width), of their longest foot. This data could be used to answer the following Research Question: How is the width of a fourth-grade student's foot related to the length? Which of the following is the y-intercept of the regression line? ## ## Simple Linear Regression## ## Correlation coefficient r = 0.6411 ## ## Equation of Regression Line:## ## length = 9.817 + 1.658 * width ## ## Residual Standard Error: s = 1.025 ## R^2 (unadjusted): R^2 = 0.411 ( ) 1.0248 ( ) 1.6576 ( ) 22.8153 ( ) 0.411 ( ) 9.8172 ( )0.6411
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…
Use the table of x and y values below to determine the slope of the least-squares regression line.
The following regression model was estimated. Q is the number of meals served, P is the average price per meal (customer ticket amount, in dollars), Rxis the average price charged by competitors (in dollars), Ad is the local advertising budget for each outlet (in dollars), and I is the average income per household in each outlet's immediate service area. Least squares estimation of the regression equation on the basis of the 25 data observations resulted in the estimated regression coefficients and other statistics given in Table below. Variable Coefficient Standard Error of Coefficient Intercept 128832.240 69974.818 Price (P) Competitor Price (Px) | Advertising (Ad) Income () -19875.954 4100.856 15467.936 459.280 0.261 0.094 8.780 1.017 Coefficient of determination R =83.3% (a) Interpret the coefficients of independent variables. (b) Test the significance of independent variables at 5% level of Significance. (c) Interpret R? with the help of adjusted R2. (d) Test for the overall…
R3.4 Stats teachers' cars A random sample of AP Statistics teachers was asked to report the age (in years) and mile- age of their primary vehicles. A scatterplot of the data, a least-squares regression printout, and a residual plot are provided below. R squared - 82.0% R squared (adjusted) -81.1% -19280 with 21 -2-19 degrees of freedom Variable Constant Carage Coefficient 7288.54 11630.6 se. of Coeff bratio prob LII 931 0.2826 6591 1249 0.0001 200 25 se 75 e.0 25 se 75 se.e Crge
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.)
70. College Costs The table lists the average tuition and fees (in constant 2014 dollars) at public colleges and universi- ties for selected years. Year 1984 1994 2004 2014 Tuition and Fees (in 2014 dollars) 12,179 16,188 7626 9386 Source: National Center for Education Statistics. (a) Find the equation of the least-squares regression line that models the data. (b) Graph the data and the regression line in the same viewing window. (c) Estimate the cost in 2009. (d) Use the model to predict the cost in 2019.
Statistical software is generally used to test the significance of a regression model. The table below shows software output for a least squares regression line. Fill in the blanks with the correct answers, using the table above. Assume a significance level of 0.05. The variable "unemp" is the_______variable. The value of the slope of the regression line is_______. The slope of the regression line is not significantly different from______because the p-value is______ which is larger than 0.05.
Help with: Determine the least-squares regression line. Test whether there is a linear relation between height and weight at the α=0.05 level of significance. What is the P Value Remove the values listed for Player 4 from the data table. Test whether there is a linear relation between height and weight. Do you think that Player 4 is influential? What is the P Value
Report the equation of the regression line and interpret it in the context of the problem
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