When performing regression analysis, all the following are required assumptions about the error termEXCEPT:Select one:15a. It should have a mean of 1O b. It should be normally distributed22c. The values of the error term should be independent29o d. The variance should be the same for all values of the independent variable36FinisNext pageVITYNEXT ACTIVITYJump to.Midterm 1JUNPs Lr12tvTAi

In a regression , the values of error term should be independent having a constant variance for all…

When performing regression analysis, all the following are required assumptions about the error term EXCEPT: Select one: o a. It should have a mean of 1 O b. It should be normally distributed O c. The values of the error term should be independent d. The variance should be the same for all values of the independent variable

When performing regression analysis, all the following are required assumptions about the error term EXCEPT: Select one: o a. It should have a mean of 1 O b. It should be normally distributed O c. The values of the error term should be independent d. The variance should be the same for all values of the independent variable

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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The following condition is necessary in order to calculate inferential statistics for regression: the variances of Y scores for different values of X are equal (homogeneity of variance). a. true b. false c. impossible to say d. true, but only for descriptive statistics
The standardized regression coefficient expresses the: a. relation between the independent and dependent variable in terms of squared units. b. strength of the correlation between the two variables that are now incorporated into a regression analysis. c. predicted change in the dependent variable in terms of standard deviations for an increase of one standard deviation in the independent variable. d. likelihood of rejecting the null hypothesis with a regression analysis
The estimated regression line is defined as the straight line that: touches the most points in the scatter diagram. minimizes the sum of the absolute deviations between the line and the corresponding observations. minimizes the sum of the squared vertical distances between each observation and the line. none of the above
In a dataset, X is the independent variable, and Y is the dependent variable. Which of the following statement is correct? None of these Regression between X and Y determines the nature of the relationship between the variables. Regression between X and Y determines whether there exists any relationship between the variables. Correlation between X and Y determines the nature of the relationship between the variables.
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.
x1 x2 x3 x4 x5 x6 bond width on bond pull strength loop height wire post height observation die height width on length the die the post 8.0 5.2 17.0 28.6 83.0 1.9 1.6 2. 8.0 5.2 19.6 29.6 94.9 2.1 2,3 3 8.3 5.8 19.8 32.4 89.7 2.1 1.8 4. 8.5 6.4 19.6 31.0 96.2 2.0 2.0 8.8 5.8 19.4 32.4 95.6 2.2 2.1 6 9.0 5.2 18.6 28.6 86.5 2.0 1.8 7 9.3 5.6 18.8 30.6 84.5 2.1 2.1 9.3 6.0 20.4 32.4 88.8 2.2 1.9 9.5 5.2 19.0 32.6 85.7 2.1 1.9 10 9.8 5.8 20.8 32.2 93.6 2.3 2.1 11 10.0 6.4 19.9 31.8 86.0 2.1 1.8 12 10.3 б.0 18.0 32.6 87.1 2.0 1.6 13 10.5 6.2 20.6 33.4 93.1 2.1 2.1 14 10.8 6.2 20.2 31.8 83.4 2.2 2.1 15 11.0 6.2 20.2 32.4 94.5 2.1 1.9 16 11.3 5.6 19.2 31.4 83.4 1.9 1.8 17 11.5 6.0 17.0 33.2 85.2 2.1 2.1 18 11.8 5.8 19.8 35.4 84.1 2.0 1.8 19 12.0 6.5 19.4 32.2 88.5 2.1 1.9 20 12.3 5.6 18.8 34.0 86.9 2.1 1.8 21 12.5 18.6 18.6 34.2 83.0 1.9 2.0 22 12.5 18.6 20.8 35.4 96.2 2.3 2.3 From the sample data above, complete the following steps.
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ANSWER D ONLY
Alpha equals 0.01 level of significance for the given sample data.
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 dollars and dollars for every additional square foot in home size. Round your answers to three decimal places and enter in increasing order.
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11. For temperature (x) and number of ice cream cones sold per hour (y). (65, 8), (70, 10), (75, 11), (80,13), (85, 12), (90, 16). Interpret the coefficient of determination. Optional Answers: 1. 88.2% of the variability in the number of cones sold is explained by the least-squares regression model. 2. 93.9% of the variability in the number of cones sold is explained by the least-squares regression model. 3. 88.2% of the variability in the temperature is explained by the least-squares regression model. 4. 93.9% of the variability in the temperature is explained by the least-squares regression model.