Weight (in tons) and fuel economy (in miles/gallon) were measured for a sample of seven dieseltrucks. The results are presented below.Weight, a8.0024.527.0014.528.512.7521.25Mileage, y7.694.974.566.494.346.244.45(a) Given the data provided, find the coefficients for the fitted regression lineý = Bot Bi(b) Write down an estimate for the error variance ².(c) Give a 95% confidence interval for E[y|x = 14] = 0+148₁.

This question is about finding the coefficients for the fitted regression line and estimating the…

Answered: Weight (in tons) and fuel economy (in…

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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Provide a detailed interpretation analysis of the regression results below. Pay attention to the main tested variables, model fit characteristics (R 2 ) and number of respondents in the sample. State what is dependent and what are independent variables. Was the hypotheses rejected or confirmed? a) H1: If a woman has a job she will have less children born b) H2: The younger a woman got married the more children she has c) H3: Education positively affects number of children to have
The following data are the monthly salaries and the grade point averages for students who obtained a bachelor's degree in mathematics. GPA: 2.6, 3.4, 3.6, 3.2, 3.5, and 2.9; Monthly Salary: 330o, 3600, 4000, 3500, 3900, and 3600. Plot the scatter diagram showing the deviations about the estimated regression line and the line y = y(bar).
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.
Consider the following data set, where y is the final grade in a math class and is the average number of hours the student spent working on math each week. hours/week X 6.5 10 11 12.5 13 14.5 15 17.5 19.5 20 Grade y 66.1 63 71.4 72.5 79.2 94.3 95 91.5 100 98 The regression equation is y = 3x + 41.3. a) Explain what the value of the slope means in this situation, where y is the final grade in a math class and is the average number of hours the student spent working on math each week. O For each additional hour per week that a student studies on average, their final grade will be about 3 points. O For each additional hour per week that a student studies on average, their final grade will be about 41.3 points higher. For each additional hour per week that a student studies on average, their final grade will be about 3 points higher. O For each additional hour per week that a student studies on average, their final grade will be about 41.3 points. b) Explain what the value of the…
Q) Plot the relationship between total operating costs and machine hours. Draw the regression line.
Calculate the regression coefficient and obtain the lines of regression for the following data: USE MICROSOFT EXCEL
A physician wishes to know whether there is a relationship between a father’s weight (in pounds) and his new born sons’ weight (in pounds). The data are given here Fathers Weight 176 145 187 210 196 142 205 215 152 145 Sons Weight 6.6 8.2 9.2 7.1 8.8 9.3 7.1 8.6 7.8 6.0 Develop the regression equation for the sample Predict the sons weight based on the father’s weight of 300, 250 and 400.
Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sq ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract of the output obtained: The regression equation is Price = B + ¢Bedroom + yHouse Size + ALot Size Predictor Сoef SE Coef т P Constant 37718 14177 2.66 ** Bedrooms 2306 6994 0.33 0.742 House Size 74.3 52.98 0.164 Lot Size -4.36 17.02 -0.26 0.798 S= 25023 R-Sq=56.0% R-Sq(adj)=54.6% Source DF MS F P Regression 3 76501718347 25500572782 Residual Error 96 60109046053 626135896 Total 99 • Is y significantly different from -0.5? Perform the F test at the 1% level, making sure to state the null and alternative hypotheses. Give an interpretation to the term “R-sq" and comment on its value.
Below are the results of Multiple Regression Analysis. Write down the interpretation of the following tables: R Model R Square .560a .314 Change Statistics F Change df1df2 1 .314 7.210 9 142 a. Predictors: (Constant), Horsepower, Wheelbase, Fuel efficiency, Width, Price in thousands, Fuel capacity, Length, Engine size, Curb weight b. Dependent Variable: Sales in thousands Adjusted R Square Model Summaryb .270 Std. Error of the Estimate 58.895390 R Square Change Sig. F Change .000
Here is a bivariate data set. Find the regression equation for the response variable y. x y 64.9 82.6 69.4 63.6 75.7 63.4 62.7 63.9 67.2 75.4 82.1 104.2 82.7 88.5 65.6 56.4 regression equation: Enter the equation in slope-intercept form with parameters accurate to three decimal places.
The data shows a systolic and a diastolic blood pressure of certain patients. Find the linear regression eqation, using the first variable (systolic) as the independent variable. Find the best predicted diastolic blood pressure for a patient with a systolic blood pressure reading of 140. Use a significance level of x Systolic Diastolic 116 82 124 88 112 72 144 95 138 96 112 76 145 88 124 76 130 90 129 94 1)Find the correlation coefficient. 2)State the appropriate critical r value to use to test the claim that the correlation between systolic blood pressure and diastolic blood pressure is significantly different from 0 3)The correlation between diastolic blood pressure and systolic blood pressure is: significant, not significant, weak, none 4)The best predicted diastolic blood pressure for a patient with a systolic blood pressure reading of 140 is closest to 1pts
Based on the data shown below, calculate the regression line. y 1 4.27 3.64 3 3.31 5.08 5.85 6. 2.42 y = [three decimal accuracy] [three decimal accuracy] 45

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