For the regression with Percent Water causing International Migration per 1000, is the result statistically significant? How do you know?AIt is impossible to tell without knowing the confidence level.BThe coefficient is highCThe p value is lowDThe coefficient is lowEThe p value is high

To know whether result is significant or not 1. we first decide level of the significance. 2.…

Answered: For the regression with Percent Water…

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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It may be a concern that market value and assets are highly correlated and hence there may be a problem with including them both as explanatory variables. The following set of output is for the regression that excludes assets from the regression above. Based on this set of output, does it seem likely that assets and market value are highly correlated, and hence does it appear that multicollinearity is a problem? Explain how you know.
Complete the statement. When all points fall on the regression line, the value of the correlation coefficient is...
Fill in the blanks.a. Positive correlations between observations of the response variable result in an underestimate of_______b. Data collected from a designed experiment is generally preferable to data obtained from_______c. Adata point whose removal has a substantial effect on one or more sample regression coefficients is called an_______
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From the parameter estimation output, which of the following is FALSE? Coefficients Standard Error t Stat p-value 0.783 0.0159 Intercept Diameter (mm) of granules of sand -2.476 -3.161 17.159 2.034 8.438 0.000065 For a one-unit increase in the independent variable, the predicted-y is decrease by – 2.476. The independent variable is significant. For a one-unit increase in the independent variable, the predicted-y is increase by 17.159. The predictor variable is significant.
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he data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 51 inches. Is the result close to the actual weight of 4 punds? Use a significance level of 0.05. thest size (inches) Veight (pounds) Click the icon to view the critical values of the Pearson correlation coefficient r. 45 43 43 52 52 352 374 275 314 440 367 Critical Values of the Pearson Correlation Coefficient r What is the regression equation? Critical Values of the Pearson Correlation Coefficient r a = 0.05 NOTE: To test Ho: p=0 against H, p#0, reject Ho if the absolute value of r is greater than the critical value in the table. y%3= x (Round to one decimal place as needed.) a = 0.01 4 0.950 0.990 0.878 0.959 0.811 0.917 0.754 0.875 8. 0.707 0.834 9. 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 13 0.553 0.684 14 0.532 0.661 15 0.514 0.641 16 0.497 0.623 17 0.606 0.590…
When there are omitted variables in your regression, then... Group of answer choices This has no effect on the estimation of the explanatory variable because the variable is omitted This will always bias the OLS estimation of the explanatory variable the estimation of the explanatory variable(s) is unaffected The OLS estimation is biased if the omitted variables are correlated with the included variable
Using the sample data from the accompanying table, complete parts (a) and (b). E Click the icon to view the data table (a) Explain why it does not make sense to construct confidence or prediction intervals based on the least-squares regression equation. Choose the correct answer below. O A. It does not make sense to construct confidence or prediction intervals based on the least-squares regression equation because there is a linear relationship between sugar content and calories in high-protein and moderate protein energy bars. O B. It does not make sense to construct confidence or prediction intervals based on the least-squares regression equation because there is no linear relationship between sugar content and calories in high-protein and moderate protein energy bars. O C. It does not make sense to construct confidence or prediction intervals based on the least-squares regression equation because the residuals are not normally distributed. (b) Construct a 95% confidence interval for…
Previous question K The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 272 pounds? Use a significance level of 0.05. $ Chest size (inches) Weight (pounds) Click the icon to view the critical values of the Pearson correlation coefficient r. O What is the regression equation? y=+x (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest şize of 40 inches? The best predicted weight for a bear with a chest size of 40 inches is pounds. (Round to one decimal place as needed.) le the result cloen to the actual uninht of 272 nounde? S Copyright © 2022 Pearson Education Inc. All rights reserved. Terms of Use | Privacy Policy. Permissions | Contact Us % F 5 41 54 44 328 528 418 T V & Y B 55 39 51 C 580 296 503 H a 4 N 00 8 144 9 N K M N ? ► 11 L…

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For the regression with Percent Water causing International Migration per 1000, is the result statistically significant? How do you know? A It is impossible to tell without knowing the confidence level. B The coefficient is high C The p value is low D The coefficient is low E The p value is high