Suppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The correlation coefficient is 0.858 and the least squares regression line isy = 0.228x +11.187. Complete parts (a) and (b) below.Height, x27.5 25.75 26.5 25.5 27.25 26.25 25.75 27.25 27 27.25 27Head Circumference, y 17.4 17.2 17.2 16.9 17.6 17.1 17.1 17.4 17.4 17.3 17.3(a) Compute the coefficient of determination, R².R² =% (Round to one decimal place as needed.)(b) Interpret the coefficient of determination and comment on the adequacy of the linear model.Approximately % of the variation in(Round to one decimal place as needed.)is explained by the least-squares regression model. According to the residual plot, the linear model appears to be

To compute the coefficient of determination, we first need to find the total sum of squares (SST)…

Answered: Suppose a doctor measures the height,…

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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o pis pe Suppose a doctor measures the height, x, and head circumference, y. of 11 children and obtains the data below. The correlation coefficient is 0.899 and the least squares regression line is y = 0.185x+ 12.276. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.4 17.1 17.2 16.9 17.4 17.1 17.1 17.3 17.3 17.3 17.4 27.75 25.75 26.75 25.75 28 26.5 25.75 26.75 27 27.25 27.25 (a) Compute the coefficient of determination, R?. R2 = % (Round to one decimal place as needed) (b) Interpret the coefficient of determination k Approximately % of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model. Enter your answer in each of the answer boxes. Save for Later DUE RTTT:DY PIVT Score: o:5SYO Tor Tv attempts 3:35 PA- a 2/22/202 Type here to search insert prt sc 4+ backsp %23 6. 8.
The following table shows the starting salary and profile of a sample of 10 2 p employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance.What is the computed R square of the resulting multiple linear regression and its interpretation? * Civil Years of Starting salary GPA service experience ratings 79.5 15000 80.1 15000 81.2 78.0 15500 81.3 79.0 16000 82.4 80.0 16200 83.4 85.0 17500 87.9 89.9 89.1 18000 90.3 16,300 84.2 17000 87.0 17900 88.1 84.1 89.0 89.2 R squared = 0.8053; This means that 80.53% of the total variation in the starting salary can be explained by its linear relationship with GPA, years of experience and civil service ratings. R squared = 0.9651; This means that 96.51% of the total variation in the starting salary can be explained by its linear relationship with GPA, years of…
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
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
We give the total variation, the unexplained variation (SSE), and the least squares point estimate b1 . Total variation = 13.459; SSE = 2.806; b1 = 2.6652 Click here for the Excel Data File Using the information given, find the explained variation, the simple coefficient of determination (r2), and the simple correlation coefficient (r). Interpret r2. (Round your answers to 3 decimal places. Round your percent to 1 decimal place.) Explained variation r2 r % of the variation in demand can be explained by variation in price differential.
State Debt and Per Capita Taxes Data for per capita state debt and per capita state tax for five randomly selected states are shown. Per capita debt 3377, 1446, 4345, 1442, 2705 Per capita tax 2432, 1860, 1535, 2147, 2376 The correlation coefficient for the data is r=-.248 and a=.05. Should regression analysis be done? The regression analysis should not be done or The regression analysis should be done. Find the equation of the regression line. Round the coefficients to at least three decimal places, if necessary y'= a+bx a= b= find y' when x=$1992. Round the answer to at least three decimal places, if necessary y'=
Fill in the blanks. a. Positive correlations between observations of the response variable result in an underestimate of ________. b. Data collected from a designed experiment is generally preferable to data obtained from ________. c. Adata point whose removal has a substantial effect on one or more sample regression coefficients is called an _________.
Suppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The correlation coefficient is 0.818 and the least squares regression line is y = 0.137x + 13.622. Complete parts (a) and (b) below. 27 25 75 26.75 25.25 27.75 26.25 26.25 27. 25 27 25 27.25 27.25 D Height, x Head Circumference, y 17.5 17.1 17.2 17.1 17.4 17.2 17.2 17.4 17.3 17.3 17.3 (a) Compute the coefficient of determination, R? R2 =% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination and comment on the adequacy of the linear model. Approximately % of the variation in V is explained by the least-squares regression model. According to the residual plot, the linear model appears to be (Round to one decimal place as needed.) arch
The following data give the family size (2) and number of pets per family (y) for a random sample of 10 families. 4. 2 6. 3. 0. 4. 9. 10 Create a scatterplot for the data. y 10 6. 7- 4 1 2 3 4 5 6 7 8 9 10 11 Clear All Draw: Determine the least squares regression line for the data. Round values to four decimal places, if necessary. Determine the correlation coefficent. Round the solution to four decimal places, if necessary. Use the model to predict the number of pets owned by a family with 13 members. Round the solution to the nearest whole number. 5. 5. 2. 3. 3.
A researcher is interested in examining the relationship between spousal abuse and child abuse. Specifically, they are interested in determining whether there is a predictive relationship between spousal abuse and child abuse in 5 county social services offices. Calculate the linear regression line for the following data. Note you have already calculated the first step to this analysis (Pearson's Correlation)
The following data represent the speed at which a ball was hit (in miles per hour) and the distance it traveled (in feet) for a random sample of home runs in a Major League baseball game in 2018. Complete parts (a) through (f). Click here to view the data. Click here to view the critical values of the correlation coefficient. (a) Find the least-squares regression line treating speed at which the ball was hit as the explanatory variable and distance the ball traveled as the response variable. y = 5x+ (5 (Round to three decimal places as needed.) (b) Interpret the slope and y-intercept, if appropriate. Begin by interpreting the slope. A. The slope of this least-squares regression line says that the distance the ball travels increases by the slope with every 1 mile per hour increase in the speed that the ball was hit. O B. The slope of this least-squares regression line shows the increase in the speed that the ball was hit with every 1 foot increase in the distance that the ball was hit.…

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