4. The following regression is fitted using variables identified that could be related to tuitioncharges ($) of a university.TUITION = a+ ẞ ACCEPT + y MSAT + 1 VSATWhere ACCEPT = the percentage of applicants that was accepted by the university, MSAT =Median Math SAT score for the freshman class and VSAT = Median English SAT score for thefreshman class.The data was processed using MNITAB and the following is an extract of the output obtained:Predictor CoefConstant-26780StDev6115TP-4.380.000ACCEPT116.0037.17*0.003MSAT-4.2114.12VSAT70.8515.77-0.304.490.767**S = 2685R-Sq = 69.6%Analysis of Variance.R-Sq (adj) = 67.7%SourceDFSSMSFPRegression380813937126937979037.370.000Residual Error493531930517208021Total521161332421a) Write out the regression equation.b) State the dependent and independent variable(s)c) Fill in the blanks identified by ** and ****.d) Is ẞ significant, at the 10% level of significance?e) State one limitation of using the regression equation for predicting the value of the GPAscore.

Given the partial output of multiple linear regression.Want to write a regression equation and…

Answered: 4. The following regression is fitted…

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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1) Match each of the five scatterplots to the appropriate correlation coefficient and equation of regression line. Explain how you know that you have made a correct match. a. r= 0.83, y= -2.1 + 1.4x d. r= -0.83, y = 11.8 – 1.4x b. r= -0.31, y = 7.8 – 0.5x e. r= 0.41, y=1.4 + 1.4x c. r= 0.96, y= -2.1 + 1.4x Scatterplot 1 Scatterplot 2 Scatterplot 3 Scatterplot 4 Scatterplot 5
The local utility company surveys 12 randomly selected customers. For each survey participant, the company collects the following: annual electric bill (in dollars) and home size (in square feet). Output from a regression analysis appears below: Bill 13.45 +4.39*Size Coefficients Estimate Std. Error (Intercept) 13.45 Size 4.39 0.54 0.2 We are 90% confident that the mean annual electric bill increases by between 4.028✔ dollars and 4.753 x dollars for every additional square foot in home size. Round your answers to three decimal places and enter in increasing order.
The fish in my pond have mean length 10 inches with a standard deviation of 2 inches and mean weight 4 pounds with a standard deviation of .6 pounds. The correlation coefficient of length and weight is .9. If the length of a particular randomly selected fish is reported to be 15 inches, then what should we predict for the weight of that fish using simple linear regression?
What kind of plot is useful for deciding whether it is reasonable to find a regression plane for a set of data points involving several predictor variables?
A real estate agent wanted to find the relationship between sale price of houses and the size of the house. Shecollected data on two variables recorded in the following table for 15 houses in Seattle. The two variables are PRICE= Sale price of houses in thousands of dollarsSIZE= Area of the entire house in square feet. The Excel working has been given. Note: the left hand side is Regression run.. The right hand side is 'new' regression run (for ans d). Question a) Using MICROSOFT EXCEL- run the above regression and copy the output into your assignment word documentfrom which you can write down the least square regression line. Write down the least square regression linefrom that specific output. b) Interpret the slope and constant term with proper UNITS assigned. c) Comment on the explanatory power of the regression model from the required output. Copy that specificoutput into your assignment word document.Now to increase the explanatory power of the model the real estate agent decides…
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A real estate agent wanted to find the relationship between sale price of houses and the size of the house. Shecollected data on two variables recorded in the following table for 15 houses in Seattle. The two variables are PRICE= Sale price of houses in thousands of dollarsSIZE= Area of the entire house in square feet. The Excel working has been given. Note: the left hand side is Regression run(ans a).. The right hand side is 'new' regression run (for ans d). Question b) Interpret the slope and constant term with proper UNITS assigned. c) Comment on the explanatory power of the regression model from the required output. Copy that specificoutput into your assignment word document.Now to increase the explanatory power of the model the real estate agent decides to look at the age of thehouse and the garden size. For the 15 houses in our sample the new variables areAGE= Age of the house in years, since it was builtGARDEN= Area of the garden in acres. d) Once these two new variables are…
The fish in my pond have mean lenth 14 inches with a standard deviation of 2 inches and mean weight 4 pounds with a standard deviation of .8 pounds. The correlation coefficient of length and weight is .4. If the length of a particular randomly selected fish is reported to be 15 inches, then what should we predict for the weight of that fish using simple linear regression?
Many high school students take either the SAT or the ACT. However, some students take both. Data were collected from 100 students who took both college entrance exams. The average SAT score was 920 with a standard deviation of 170. The average ACT score was 20 with a standard deviation of 5. The correlation coefficient r between these two variables equals 0.82. To predict the SAT score from a student’s ACT score, what is the equation of the least-squares regression line? Please show your work.
The Cadet is a popular model of sport utility vehicle, known for its relatively high resale value. The bivariate data given below were taken from a sample of fifteen Cadets, each bought "new" two years ago and each sold "used" within the past month. For each Cadet in the sample, we have listed both the mileage, x (in thousands), that the Cadet had on its odometer at the time it was sold used, and the price, y (in thousands of dollars), at which the Cadet was sold used. These data are shown graphically in the scatter plot in Figure 1. Mileage, x(in thousands) Used selling price, y(in thousands of dollars) 21.1 31.2 34.2 25.8 23.3 34.1 37.5 22.8 29.1 27.1 24.2 29.7 23.7 28.0 27.7 25.1 24.1 27.6 23.2 30.9 26.7 31.7 28.1 30.0 20.9 31.6 15.2 34.6 25.7 26.6 The least-squares regression line for these data has a slope of approximately −0.5. Answer the following. Carry your intermediate computations to at least four decimal places, and round your answers as…
The following regression is fitted using variables identified that could be related to student requested loan amount, LOAN-AMT(S) for returning students of a certain University. LOAN - AMT = a + B ACCEPT + y PREV + OUTS Where ACCEPT = the percentage of applicants that was accepted by the university, PREV= previous loan amount and OUTS-outstanding loan amount The data was processed using MNITAB and the following is an extract of the output obtained: Predictor Constant ACCEPT PREV OUTS S = 2685 Coef -26780 116.00 -4.21 70.85 Analysis of Variance R-Sq 69.6% Source DE SS Regression 3 Residual Error 49 Total 52 EXHIBIT 2 StDev 6115 37.17 14.12 15.77 808139371 353193051 1161332421 T * 3.14 -0.30 4.49 MS 269379790 7208021 a) What is dependent and independent variables? b) Fully write out the regression equation c) What is the sample size used in this investigation? d) Fill in the blanks identified by *' and ****. e) Is B significant, at the 5% level of significance? P 0.000 0.003 ** 0.000…
Suppose a car's city miles per gallon rating can be determined by the car's weight. The means and standard deviations of these variables and the correlation coefficient between them are reported in the following table. Determine the coefficients of the least squares line for predicting a car's miles per gallon rating from its weight. Report the equation of this line. 2 decimals for "a" and 5 decimals for "b"

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