2. Using the data given below, test the utility of the sample regression model using a = 0.01,Analyze using pearson R and Spearman rankx112.3 97.0 92.7 86.0 102.0 99.2 95.8 103.5 89.0 86.775.0 71.0 57.7 48.7 74.3 73.3 68.0 59.3 57.8 48.5Ľ

Answered: 2. Using the data given below, test 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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Suppose a doctor measures the height, x, and head circumference, y, of 11 children and obtains the data below. The correlation coefficient is 0.883 and the least squares regression line is y = 0.134x + 13.693. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.4 27.75 25.25 26 25.25 27.25 26.75 26 27.25 27 27.25 26.75 17.1 17.3 17.0 17.4 17.2 17.2 17.3 17.3 17.4 17.3 ..... (a) Compute the coefficient of determination, R?. R? % (Round to one decimal place as needed.) (b) Interpret the coefficient of determination. Approximately % of the variation in is explained by the least-squares gression model. (Round to one decimal place as needed.)
o pis pe Suppose a doctor measures the height, x, and head circumference, y. of 11 children and obtains the data below. The correlation coefficient is 0.899 and the least squares regression line is y = 0.185x+ 12.276. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.4 17.1 17.2 16.9 17.4 17.1 17.1 17.3 17.3 17.3 17.4 27.75 25.75 26.75 25.75 28 26.5 25.75 26.75 27 27.25 27.25 (a) Compute the coefficient of determination, R?. R2 = % (Round to one decimal place as needed) (b) Interpret the coefficient of determination k Approximately % of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model. Enter your answer in each of the answer boxes. Save for Later DUE RTTT:DY PIVT Score: o:5SYO Tor Tv attempts 3:35 PA- a 2/22/202 Type here to search insert prt sc 4+ backsp %23 6. 8.
Q1 Collect sufficient data about any two quantitative variables (logically correlated) using reasonable sets of values (At least 20 values). Use Microsoft Excel and answer the following: First: Determine the independent variable and the dependent variable. Second: Make the correlation analysis, determine the correlation coefficient, and interpret it. Third: Conduct the regression analysis and answer the following questions: What is the type of regression in your example? Write the sample size. Find the degrees of freedom. Find the value of the coefficient of determination, and interpret it. Is your model valid? Why? Is the independent variable having a significant effect on the dependent variable? Why? Write down the regression line equation. Estimate the value of ŷ at any value of X.
Consider the following ANOVA table for a multiple regression model relating housing prices (in thousands of dollars) to the number of bedrooms in the house and the size of the lot on which the house was built (in square feet). There were 9090 total observations. Estimated Price=20,160.07+2188.83(Bedrooms)+0.2139(Lot Size)Estimated Price=20,160.07+2188.83(Bedrooms)+0.2139(Lot Size) ANOVA dfdf SSSS MSMS F� Significance F� Regression 22 306,443.7975306,443.7975 153,221.8988153,221.8988 21.727421.7274 2.2211E-082.2211E-08 Residual 8787 613,525.5190613,525.5190 7052.01757052.0175 Total 8989 919,969.3165919,969.3165 What percent of variation in housing prices is explained by the number of bedrooms and lot size? Round your answer to two decimal places
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Suppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The correlation coefficient is 0.858 and the least squares regression line is y = 0.228x +11.187. Complete parts (a) and (b) below. Height, x 27.5 25.75 26.5 25.5 27.25 26.25 25.75 27.25 27 27.25 27 Head Circumference, y 17.4 17.2 17.2 16.9 17.6 17.1 17.1 17.4 17.4 17.3 17.3 (a) Compute the coefficient of determination, R². R² =% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination and comment on the adequacy of the linear model. Approximately % of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model. According to the residual plot, the linear model appears to be

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2. Using the data given below, test the utility of the sample regression model using a = 0.01, Analyze using pearson R and Spearman rank 112.3 97.0 92.7 86.0 102.0 99.2 95.8 103.5 89.0 86.7 75.0 71.0 57.7 48.7 74.3 73.3 68.0 59.3 57.8 48.5