A data set is given below.(a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y.(b) Given that x = 3.8333, sx = 2.0412, y = 4.3167, sy = 1.3363, and r= -0.9153, determine the least-squares regressionline.(c) Graph the least-squares regression line on the scatter diagram drawn in part (a).Xy1 2 4 45.4 5.9 5.0 4.0(a) Choose the correct graph below.O A.QQ2B.There appears to be a linear, negative relationship.(b) y = -0.599 x + (6.614)(Round to three decimal places as needed.)(c) Choose the correct graph below.6 62.6 3.0B.QQLQC.QLD.QQLQ

The dataset on x and y is given. Sample size (n) = 6 x¯=3.8333sx=2.0412y¯=4.3167sy=1.3363r=-0.9153…

Answered: (a) Draw a scatter diagram. Comment on…

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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(b) For the (x, y) data set of part (a), compute the equation of the sample least-squares line ŷ = a + bx. (Use 4 decimal places.) a b If the per capita spending was x = $39 one year, what do you predict for the spending the next year? (Use 2 decimal places.) $ per capita (c) Compute the sample correlation coefficient r and the coefficient of determination r2. (Use 4 decimal places.) r r2 Test ρ > 0 at the 1% level of significance. (Use 2 decimal places.) t critical t
(a) The correlation coefficient: r = (b) The least squares line: ỹ = %3D
A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y. (b) Given that x= 3.6667, sy = 2.2509, y= 3.6833, s, = 1.8809, and r= - 0.9511, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a). 1 4 4 6 6 y 5.0 6.3 4.2 3.4 1.4 1.8 (a) Choose the correct graph below. OA. B. OC. OD. Ay 74 Ay Ay 7- .. .. There appears to be a linear, negative relationship. (b) y=x+ O (Round to three decimal places as needed.) (c) Choose the correct graph below. O A. B. OC. D. Ay 0-
A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y (b) Given that x =3.5000, s, = 2.2583, y = 4.4667, s, = 1.7682, and r= -0.9416, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a). 6 3 4 5.4 68 5.6 4.0 2.3 2.7 1 y (a) Choose the correct graph below. O A Oc. Q There appears to be V relationship (b) y=+ O (Round to three decimal places as needed.) (c) Choose the correct graph below. O A OB. OC. OD.
7
A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y. (b) Given that x = 3.6667, sx =2.4221, y = 3.8667, sy = 1.8435, andr= -0.9525, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a). D O A. (a) Choose the correct graph below. Ay 6- X y 0 0 2 3 5 6 6 5.8 5.7 5.0 2.8 1.7 2.2 O G B. Ay 6- Q (...) C. 0- ● Q D. Ау 0- X 6
A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y. (b) Given that x=3.8333, sx=2.4014, y=3.6500, sy=1.7942, and r=−0.9539, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a).
A landscaping company has collected data on home values (in thousands of $) and expenditures (in thousands of $) on landscaping with the hope of developing a predictive model to help marketing to potential new clients. Suppose the following table represents data for 14 households. Home Value Landscaping Expenditures ($1,000) ($1,000) 241 8.2 322 10.7 197 12.1 340 16.3 300 15.7 400 18.8 800 23.5 200 9.5 522 17.5 546 22.0 438 12.2 463 13.5 635 17.8 357 13.8 (a) Develop a scatter diagram with home value as the independent variable. 900 900 800 800 20 20 700 700 600 600 15 15 500 500 400 400 300 300 200 200 100 100 100 200 300 400 500 600 700 800 900 10 15 20 25 100 200 300 400 500 600 700 800 900 5 10 15 20 25 Home Value ($1,000) Landscaping Expenditures ($1,000) Home Value ($1,000) Landscaping Expenditures ($1,000) Landscaping Expenditures ($1,000) Home Value ($1,000) Landscaping Expenditures ($1,000) Home Value ($1,000)
Consider data on heights of husbands and wives for a sample of 199 married couples in the UK collected by the Great Britain Office of Population Census and Surveys.[1] The scatter plot below shows wife height plotted against husband height and the least-squares regression line is shown in red. The equation of the regression line is: WÊin = 40.49 + 0.33H Hin where W Hin is the wife's height and HHin is the husband's height. Both are measured in inches. R 65 Wife's Height (inches) 60 65 70 Husband's Height (inches) 75 O Now consider a new variable for husband height measured centimeters called HHcm. Because there are 2.54 cm per inch, this variable is defined as HHcm = 2.54* HHin. Suppose we use the exact same sample, but instead estimate a regression line with husband height in centimeters while wife height is still measured in inches: WHin = a + bHHcm How tall does a husband have to be in inches? Use the original regression equation provided for the regression to predict that his wife…
A pediatrician wants to determine the relationship that exists between achild’s height, x, and head circumference, y. She randomly selects 11 children from her practice, measures their heights and head circumferences, and conducts the least-squares regression analysis with the simple linear model using StatCrunch. The output is given below: (a) Write down the equation of the least-squares regression line treating height as the explanatory variable and head circumference as the response variable. (b) Interpret the slope and y-intercept, if appropriate. (c) Use the regression equation to predict the head circumference of a child who is 25 inches tall. Assume that the regression model is applicable.(d) It is observed that one child who is 25 inches tall has a head circumference of 17.5 inches. Is the observed value above or below average among all children with heights of 25 inches?
Absences and Final Exam Scores No. of absences, x 0 1 For students WHO IIISS THO Classes is et the slope or the y-intercept. = as needed.) Final exam score, y 88.9 86.6 83.6 81.5 student who misses five class periods. 2 Print 3 = needed.) ow average for this number of absences? 4 5 78.2 73.7 Done 6 7 8 63.9 72.7 It is not appropriate to interpret the slope. 9 65.3 65.4 0 O X Reference 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 0.997 0.950 0.878 0.811 0.754 0.707 0.666 0.632 0.602 0.576 0.553 0.532 0.514 0.497 0.482 0.468 0.456 0.444
A random sample of 65 high school seniors was selected from all high school seniors at a certain high school. The following scatterplot shows the height, in centimeters (cm), and the foot length, in cm, for each high school senior from the sample. The least-squares regression line is shown. The computer output from the least-squares regression analysis is also shown. Term Coef (SE) Coef T-value P-value Constant 105.08 6.00 17.51 0.000 Foot Length 2.599 0.238 10.92 0.000 S=5.90181 R-sq= 65.42% (a) Calculate and interpret the residual for the high school senior with a foot length of 20cm and a height of 160cm. (b) The standard deviation of the residuals is s=5.9. Interpret the value in context. (c) The following histogram summarizes the 65 residuals. Assume that the distribution of residuals is approximately normal with mean 0cm and standard deviation5.9cm. What percent of the residuals are greater than 8cm? Justify your answer. (d) Based on your answer to part (c), would…

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