Which is true about the Pearson correlation and simple linear regression? Both imply causality None of...
Which is true about the Pearson correlation and simple linear regression?
Both imply causality
None of the options
Both can be expanded to include multiple independent variables
Both easily allow for prediction
Homework Answers
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Which is true about the Pearson correlation and simple linear
regression?
Both imply causality
None of...
Answer both questions please true or false 16. The slope of the simple linear regression equation...
Answer both questions please true or false 16. The slope of the simple linear regression equation represents the average change in the value of the dependent variable per unit change in the independent variable (X). True/False 19. When using simple regression analysis, if there is a strong correlation between the independent and dependent variable, then we can conclude that an increase in the value of the independent variable causes an increase in the value of the dependent variable.
8. In linear regression, the confidence interval can be wider than the prediction interval. a. True...
8. In linear regression, the confidence interval can be wider than the prediction interval. a. True b. False 9. In a regression and correlation analysis if R-1, then a. SSg - SSI b. SSg - 1 c. SSR ESSE d. SSR SS 10. A multiple regression model has: a. only one independent variable b. more than one dependent variable c. more than one independent variable d. none of the above
Which of the following is FALSE about Correlations: We can use the Pearson Correlation Coefficient when...
Which of the following is FALSE about Correlations: We can use the Pearson Correlation Coefficient when both variables are measured on an interval or ratio scale A correlation examines the relation between two variables The Pearson Correlation Coefficient describes the relation between two variables in terms of the strength and direction of the relationship. A correlation implies causation
9) Which of the following statements about building multiple regression models is true? (4) A) No...
9) Which of the following statements about building multiple regression models is true? (4) A) None of these. B) When comparing among competing multiple regression models, it is best to choose a small value of R2 regression model. have the highest values for se C) It is always preferable to include more rather than fewer predictor variables in a multiple D) When comparing among competing multiple regression models, the best models will
9) Which of the following statements about building...
Select all of the following statements that are true about linear regression analysis of quantitative variables....
Select all of the following statements that are true about linear regression analysis of quantitative variables. If the purpose of our regression model is prediction, it does not matter which variables we define as the explanatory and response variable. The observed values of Y will fall on the estimated regression line, while the predicted values of Y will vary around the regression line. The purpose of linear regression is to investigate if there exists a linear relationship between a response...
Which of the following statements regarding regression and correlation are true? (There may be more than...
Which of the following statements regarding regression and correlation are true? (There may be more than one correct answer.) a. If the linear correlation between two variables is 0, then there is no relationship between the two variables. b. When the slope of a linear regression equation is near 0, then the linear correlation between the two variables must also be near 0. c. The average error between the actual values and the predicted values of a least squares line...
2 pts. when regression line has no slope, we can still predict Y from X because...
2 pts. when regression line has no slope, we can still predict Y from X because the line still has a y intercept. A. True B. False 34. 2 pts. Can we infer causality between two variables solely on the basis of their correlation? A. Yes, we can infer causality. B. No, we cannot infer causality. 35. 2 pts. Which of the following is the fundamental task of regression? A. Correctly plotting all of the points on a scatter plot....
Which of the following statements regarding regression and correlation are true? (There may be more than...
Which of the following statements regarding regression and correlation are true? (There may be more than one correct answer.) a. A value of the linear correlation, r, near -1 means the data is tightly bundled around a line, and predictions within the scope of data are very reliable. b. When the slope of a linear regression equation is near 0, then the linear correlation between the two variables must also be near 0. c. The average error between the actual...
1. Which of the following is correct? A. In correlation analysis there are two variables and...
1. Which of the following is correct? A. In correlation analysis there are two variables and both are dependent B. I n correlation analysis there are two variables and both are independent C. I n regression analysis there are two variables and both are dependent D: In regression analysis there are two variables and both are independent 2. measures the strength of linear association between two variables. A. Regressor B. Regressand C. Correlation coefficient D. None 3. the independent variables....
1. Choose all the valid answers to the description about linear regression and logistic regressio...
machine learning/ stats questions
1. Choose all the valid answers to the description about linear regression and logistic regression from the options below: A. Linear regression is an unsupervised learning problem; logistic regression is a super- vised learning problem. B. Linear regression deals with the prediction of co ontinuous values; logistic regression deals with the prediction of class labe C. We cannot use gradient descent to solve linear regression: we must resort to least square estimation to compute a closed-form...
8. In linear regression, the confidence interval can be wider than the prediction interval. a. True b. False 9. In a regression and correlation analysis if R-1, then a. SSg - SSI b. SSg - 1 c. SSR ESSE d. SSR SS 10. A multiple regression model has: a. only one independent variable b. more than one dependent variable c. more than one independent variable d. none of the above
9) Which of the following statements about building multiple regression models is true? (4) A) None of these. B) When comparing among competing multiple regression models, it is best to choose a small value of R2 regression model. have the highest values for se C) It is always preferable to include more rather than fewer predictor variables in a multiple D) When comparing among competing multiple regression models, the best models will
9) Which of the following statements about building...
Select all of the following statements that are true about linear regression analysis of quantitative variables. If the purpose of our regression model is prediction, it does not matter which variables we define as the explanatory and response variable. The observed values of Y will fall on the estimated regression line, while the predicted values of Y will vary around the regression line. The purpose of linear regression is to investigate if there exists a linear relationship between a response...
2 pts. when regression line has no slope, we can still predict Y from X because the line still has a y intercept. A. True B. False 34. 2 pts. Can we infer causality between two variables solely on the basis of their correlation? A. Yes, we can infer causality. B. No, we cannot infer causality. 35. 2 pts. Which of the following is the fundamental task of regression? A. Correctly plotting all of the points on a scatter plot....
1. Which of the following is correct? A. In correlation analysis there are two variables and both are dependent B. I n correlation analysis there are two variables and both are independent C. I n regression analysis there are two variables and both are dependent D: In regression analysis there are two variables and both are independent 2. measures the strength of linear association between two variables. A. Regressor B. Regressand C. Correlation coefficient D. None 3. the independent variables....
machine learning/ stats questions
1. Choose all the valid answers to the description about linear regression and logistic regression from the options below: A. Linear regression is an unsupervised learning problem; logistic regression is a super- vised learning problem. B. Linear regression deals with the prediction of co ontinuous values; logistic regression deals with the prediction of class labe C. We cannot use gradient descent to solve linear regression: we must resort to least square estimation to compute a closed-form...
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