A statistical program is recommended.Consider the following data for a dependent variable y and two independent variables, x, and x,.X1X21294471010825171125116178409451191757170361211759131427616211The estimated regression equation for the data isý = -18.4 + 2.01x, + 4.74x2.(a) Develop a 95% confidence interval for the mean value of y when x, = 51 and x, = 16. (Round your answers to three decimal places.)to(b) Develop a 95% prediction interval for y when x, = 51 and x, = 16. (Round your answers to three decimal places.)to3074

Given: x1 x2 y 30 12 94 47 10 108 25 17 112 51 16 178 40 5 94 51 19 175 74 7…

Answered: A statistical program is recommended.…

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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The following correlations were computed as part of a multiple regression analysis that used education, job, and age to predict income. Income Education Job Age Income 1.000 Education 0.677 1.000 Job 0.173 −0.181 1.000 Age 0.369 0.073 0.689 1.000 Which is the dependent variable? Multiple Choice Income Age Education Job
Seven North American Green Frogs (Rana clamitans) had their jumping distance recorded (in mm) multiple times in a laboratory. The mean jumping distance for these frogs along with their length (measured from snout to vent in miMillimeters) are presented in the table below. Length of Frog 52 68 37 65 77 81 59 Mean Jumping Distance 546 673 415 659 793 814 563 (a) Determine the linear regression model that will best predit the mean jumping distance of a North American Green Frog based on the frog's length. (b) How well does the linear regression model fit this sample data? (c) Use the linear regression model to predict the mean jumping distance of a North American Green Frog that is 48 mm in length. No excel, please.
Here is a bivariate data set. Find the regression equation for the response variable y. X y 77.5 -71.4 20.2 48 37.8 142.4 40.5 109.5 -7.6 83.5 102.1 16.8 105.1 156.6 20.1 111.9 97.3 -18.6 45.2 This dataset can be downloaded as a *.csv file with this link: Download CSV regression equation: 70.2 46.4 65 61.4 66.5 67.8 47.4 79.5 57.8 68.2 56.1 55.2 69.8 87.3 64.8 65.1 49.1 60.4 56.7 Enter the equation in slope-intercept form with parameters accurate to three decimal places.
he 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 39inches. Is the result close to the actual weight of 126 pounds? Use a significance level of 0.05. Chest size (inches) 44 41 41 55 51 42 Weight (pounds) 213 206 176 309 300 178 Critical Values of the Correlation Coefficient r n α=0.05 α=0.01 NOTE: To test H0: ρ=0 against H1: ρ≠0, reject H0if the absolute value of r is greater than the critical value in the table. 4 0.950 0.990 5 0.878 0.959 6 0.811 0.917 7 0.754 0.875 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 13 0.553 0.684 14 0.532 0.661 15 0.514 0.641 16 0.497 0.623 17 0.482 0.606 18 0.468 0.590 19…
The data is given as follow. xi 2 6 9 13 20 Vi 7 18 9 26 23 The estimated regression equation for these data is y7.6 + .9x. Compute SSE, SST, and SSR (to 1 decimal) SSE SST SSR What percentage of the total sum of squares can be accounted for by the estimated regression equation (to 1 decimal)? What is the value of the sample correlation coefficient (to 3 decimals)?
Listed below are paired data consisting of movie budget amounts and the corresponding amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $125 million. Use a significance level of alpha = 0.05. %3D Budget ($) in Millions 38 116 71 67 9. 60 120 154 Gross ($) in 108 103 129 110 54 96 212 287 Millions O A. The regression equation is y = 30.9 + 1.3x; Best predicted gross of $137.4 million В. The regression equation is y = 1.3 + 30.9x; Best predicted gross of $3863.8 million C. The regression equation is y = 1.3 + 30.9x; Best predicted gross of $137.4 million D. The regression equation is y = 30.9 + 1.3x; Best predicted gross of $193.4 million Click to select your answer. ?
The following table gives the data for the average temperature and the snow accumulation in several small towns for a single month. Determine the equation of the regression line, >= bo + b₁x. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making predictions at the 0.05 level of significance. Critical Values of the Pearson Correlation Coefficient Average Temperatures and Snow Accumulations 42 33 15 44 35 15 34 8 18 25 9 14 28 26 11 25 Average Temperature (°F) Snow Accumulation (in.) 35 43 20 10
For the data given in the table below, find the linear correlation coefficient r and the least-squares regression line x y ------- 1 18 3 13 3 9 6 6 7 4 -------
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Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $120 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 40 20 118 67 71 48 119 62 8. 64 128 18 11 147 4 O 115 21 112 67 120 119 93 102 51 114 219 34 11 287 43 Click the icon to view the critical values of the Pearson correlation coefficient r. В... The regression equation is y =+x. (Round to one decimal place as needed.)
Let x be the weight of a car (in hundreds of pounds), and let y be the miles per gallon (mpg). Suppose a car weighs 3800 pounds. What does the data forecast for the miles per gallon expected? x= 27 44 32 47 23 40 34 52 y= 30 19 24 13 29 17 21 14 State the correlation coefficient and state the regression lin equation.

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