a. Make a 95% confidence interval for B. Round your answers to three decimal places. to i b. It is well known that each additional gram of carbohydrate adds 4 calories. Sugar is one type of carbohydrate. Using a regression equation for the data in the table, test at the 1% significance level whether Bis different from 4. Based on a 1% significance level test, we conclude that B different from 4. eTextbook and Media is is not

a. Make a 95% confidence interval for B. Round your answers to three decimal places. to i b. It is well known that each additional gram of carbohydrate adds 4 calories. Sugar is one type of carbohydrate. Using a regression equation for the data in the table, test at the 1% significance level whether Bis different from 4. Based on a 1% significance level test, we conclude that B different from 4. eTextbook and Media is is not

Name: The table provides details on the amount of sugar (in grams) and the
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Description: The table provides details on the amount of sugar (in grams) and the calorie count in one serving for a sample of 13 varieties of cereal.| Sugar (grams) | 4 | 13 | 13 | 11 | 7 | 6 | 6 | 2 | 7 | 12 | 20 | 3 | 15 ||---------------|---|----|----|----|-

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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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.
A company wishes to estimate a regression line for the relationship between sales and advertising. а. To arrive at its decision regarding the best model to use, the company has calculated the following three correlation coefficients. i. ii. The sales in any month depend on that month's advertising with r = 0.28 The sales in any month depend on 50% of the previous month's advertising and 50% of that month's advertising with r= 0.68 The sales in any month depend on the previous month's advertising with r = 0.92 iii. Interpret each of the above correlation coefficients and state which of the suggested models you would choose as the basis for predicting sales. Justify your answer.
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.
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