Fit a linear regression model for the following data.Assign Temperature to be factor affecting Proportion of ImpuritiesTemperature (°C) Proportion of Impurities-260.50.425-255.70.224-264.60.453-265.00.475-270.00.705-272.00.860-272.50.935-272.60.961-272.80.979- 272.90.990Define the model's slope and intercept.Slope = 0.045, intercept = 11.325None of the choices.Slope = -11.325, intercept = -0.045Slope = -11.325, intercept = 0.045Slope = -0.045, intercept = -11.325

Regression: The regression analysis is conducted here by using EXCEL. The software procedure is…

Answered: Fit a linear regression model for the…

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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You are studying the relationship between age and lung function measured as forced expiratory volume in 1 min. In a regression analysis is lung function the best option for Y? O Yes O No
Researchers studying tigers collected data on the length (in meters) and weight (in kilograms) of the animals. Is there statistically significant evidence that the length of tigers is related to their weight?
Consider the following time series: Quarter Year 1 Year 2 Year 3 1 69 66 60 2 44 36 46 3 60 62 55 4 79 82 73 (a) Choose a time series plot. (i) 100 80 60 40 20 3. 4 6 7 Period(t) 9 10 11 12 (ii) 100 80 60 40 20 1 2 3. 4 6 7 Period (t) 10 11 12
The least-squares regression equation is y 833.6x + 11,122 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7897. Complete parts (a) through (d). 55000 20000- 1s 20 25 30 35 40 4s 50 55 60 Bachelor's % (a) Predict the median income of a region in which 30% of adults 25 years and older have at least a bachelor's degree. |(Round to the nearest dollar as needed.) Median Income
The least-squares regression equation is y = 743.3x+ 12,990 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7921. Complete parts (a) through (d). 55000- 20000- 15 20 25 30 35 40 45 50 55 60 Bachelor's % (a) Predict the median income of a region in which 20% of adults 25 years and older have at least a bachelor's degree. $ (Round to the nearest dollar as needed.) Median Income
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A graphing calculator is recommended. When laboratory rats are exposed to asbestos fibers, some of them develop lung tumors. The table lists the results of several experiments by different scientists. Asbestos exposure (fibers/mL) y = 50 Mice with Tumors (%) 400 O 500 900 1,100 1,600 1,800 2,000 3,000 3000 2500 2000 1500 (a) Find the regression line for the data. (Use x for asbestos exposure in fibers/mL and y for percent of mice with tumors. Round your values to four decimal places.) 1000 500 Percent of mice that develop lung tumors (b) Construct a scatter plot and graph the regression line. o 0 7 6 11 10 27 41 38 37 49 20 30 40 50 Asbestos Exposure (Fibers/mL.) 60 Mice with Tumors (%) 3000 ● 2500 2000 1500 1000 500 60 0 0 10 20 30 40 50 60 Asbestos Exposure (Fibers/mL) Ⓡ 4
Let price denote a price index for the goods sold by a restaurant, advert the amount spent on advertising, sales the sales for the restaurant, and consider the following two regressions First regression: sales = B1 + B2price + B3price? + B4advert + ßsadvert? + e, Second regression: sales = B1 + B2price + B3price? + e We estimate both regressions using a sample of 105 observations. The sum of square residuals (E ê) from the first regression equals 50, while the sum of square Li=1 residuals from the second regression equals 70. Suppose we are interested in testing the null hypothesis that expected sales do not depend on advertising. What is the F- statistic for this null hypothesis? Recall the F-statistic is given by ((SSER - SSEU)/J)/(SSEy/(n – K)). O a. -15 O b. 42 Oc. 21 O d. 20 O e. All other options are incorrect.
I need help to interpret the slope of the scatter plot and to do the linear regression equation
13) Use computer software to find the multiple regression equation. Can the equation be used for prediction? An anti-smoking group used data in the table to relate the carbon monoxide( CO) of various brands of cigarettes to their tar and nicotine (NIC) content. 13). CO TAR NIC 15 1.2 16 15 1.2 16 17 1.0 16 6. 0.8 1 0.1 1 8. 0.8 8. 10 0.8 10 17 1.0 16 15 1.2 15 11 0.7 9. 18 1.4 18 16 1.0 15 10 0.8 9. 0.5 18 1.1 16 A) CO = 1.37 + 5.50TAR – 1.38NIC; Yes, because the P-value is high. B) CÓ = 1.37 - 5.53TAR + 1.33NIC; Yes, because the R2 is high. C) CO = 1.25 + 1.55TAR – 5.79NIC; Yes, because the P-value is too low. D) CO = 1.3 + 5.5TAR - 1.3NIC; Yes, because the adjusted R2 is high. %3D
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Fit a linear regression model for the following data.

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