Homework Answers
1. Dummy variable is used by taking the value 0 or 1 to incorporate the effect of a categorical variable
C) A dummy variable
2. The adjusted multiple coefficients of determination adjust the number of independent variables.
B) the number of independent variables
3. Z = X1X2 is called an interaction effect.
B) Interaction
4. F test is used to determine whether one additional variable makes a significant contribution to a multiple regression model.
C) An F test
1. (4pt) A variable that takes on the values of 0 or 1 and is used...
1. (4pt) A variable that takes on the values of 0 or 1 and is used to incorporate the effect of categorical variables in a regression model is called a. a constant variable b. a dummy variable c. an interaction d. None of these alternatives are correct. 2. (4pt) The model y = Bo + B1X1 + B2X2 +E is called a. First-order model with one predictor variable b. First-order model with two predictor variables c. Second-order model with two...
1) In a multiple regression output, if individual test of slope coefficient for each variable shows...
1) In a multiple regression output, if individual test of slope coefficient for each variable shows that all the independent variables are not significant individually, but test on overall validity of model supports the alternative hypothesis at a specified level of significance, this is most likely due to: A. autocorrelation B. multicollinearity C. the presence of dummy variables D. the absence of dummy variables 2.
4. +pt) When dealing with the problem of non-constant variance, the log transformation means using a....
4. +pt) When dealing with the problem of non-constant variance, the log transformation means using a. 1/X as the independent variable instead of X b. LogX as the independent variable instead of X c. Logy as the dependent variable instead of Y d. 1/Y as the dependent variable instead of Y 5. (4pt) A variable such as Z, whose value is Z = X1X2 is added to a general linear model in order to account for potential effects of two...
1. In order to test whether the multiple linear regression model y bo +b,x1 + b2X2 is better than the average model (lazy model), which of the following null hypotheses is correct: a. Ho' b1...
1. In order to test whether the multiple linear regression model y bo +b,x1 + b2X2 is better than the average model (lazy model), which of the following null hypotheses is correct: a. Ho' b1 = b2 = 0 Но: B1 B2-0 с. We have a dataset Company with three variables: Sales, employees and stores. To build a multiple linear regression model using Sales as dependent variable, number of stores and number of employees as independent variables, which of the...
7. (4pt) A term used to describe the case when the independent variables in a multiple...
7. (4pt) A term used to describe the case when the independent variables in a multiple regression model are correlated is a. regression b. correlation c. multicollinearity d. None of the above answers is correct 8. (4pt) A variable that cannot be measured in numerical terms is called a. a nonmeasurable random variable b. a constant variable c. a dependent variable d. a categorical variable 9. The following regression model has been proposed to predict sales at a computer store....
HELP ASAP Suppose you are wishing to fit a multiple linear regression model using one categorical...
HELP ASAP
Suppose you are wishing to fit a multiple linear regression model using one categorical variable that can take on 17 different values. For example, if you wished to use the months of the year in your model, the categorical variable "month" would have 12 different values: January, February, March, etc. In general, how many dummy variables would you need to incorporate into your model to completely capture the effect of all 17 conditions of a categorical variable on...
multiple choice 1. Average weekly claims for unemployment insurance, money supply and the index of stock...
multiple choice 1. Average weekly claims for unemployment insurance, money supply and the index of stock prices are all examples of A) coincident indicators. B) leading indicators. C) lagging indicators. D) None of the above 2. The use of a dummy variable in regression analysis indicates A) that insufficient data is available for the analysis. B) that a researcher does not really know what to include in the equation. C) the use of hypothetical data. D) that a categorical variable...
Suppose we have the following values for a dependent variable, Y, and three independent variables, X1,...
Suppose we have the following values for a dependent variable, Y, and three independent variables, X1, X2, and X3. The variable X3 is a dummy variable where 1 = male and 2 = female: X1 X2 X3 Y 0 40 1 30 0 50 0 10 2 20 0 40 2 50 1 50 4 90 0 60 4 60 0 70 4 70 1 80 4 40 1 90 6 40 0 70 6 50 1 90 8 80 ...
Decide (with short explanations) whether the following statements are true or false. e) In a simple linear regression model with explanatory variable x and outcome variable y, we have these summary s...
Decide (with short explanations) whether the following
statements are true or false.
e) In a simple linear regression model with explanatory variable x and outcome variable y, we have these summary statisties z-10, s/-3 sy-5 and у-20. For a new data point with x = 13, it is possible that the predicted value is y = 26. f A standard multiple regression model with continuous predictors and r2, a categorical predictor T with four values, an interaction between a and...
1. Which of the following conditions will lead to a smaller variance for the intercept estimator...
1. Which of the following conditions will lead to a smaller variance for the intercept estimator for your multiple regression model? (A) X values cluster far from the origin of the X axis (B) X values closely pack around the mean of X in your sample (C) Small sample sizes (D) High correlation among the explanatory variables (E) Small error variance in the population regression function 2. R-squared (A) measures the proportion of variability of the dependent variable that is...
1. (4pt) A variable that takes on the values of 0 or 1 and is used to incorporate the effect of categorical variables in a regression model is called a. a constant variable b. a dummy variable c. an interaction d. None of these alternatives are correct. 2. (4pt) The model y = Bo + B1X1 + B2X2 +E is called a. First-order model with one predictor variable b. First-order model with two predictor variables c. Second-order model with two...
4. +pt) When dealing with the problem of non-constant variance, the log transformation means using a. 1/X as the independent variable instead of X b. LogX as the independent variable instead of X c. Logy as the dependent variable instead of Y d. 1/Y as the dependent variable instead of Y 5. (4pt) A variable such as Z, whose value is Z = X1X2 is added to a general linear model in order to account for potential effects of two...
1. In order to test whether the multiple linear regression model y bo +b,x1 + b2X2 is better than the average model (lazy model), which of the following null hypotheses is correct: a. Ho' b1 = b2 = 0 Но: B1 B2-0 с. We have a dataset Company with three variables: Sales, employees and stores. To build a multiple linear regression model using Sales as dependent variable, number of stores and number of employees as independent variables, which of the...
7. (4pt) A term used to describe the case when the independent variables in a multiple regression model are correlated is a. regression b. correlation c. multicollinearity d. None of the above answers is correct 8. (4pt) A variable that cannot be measured in numerical terms is called a. a nonmeasurable random variable b. a constant variable c. a dependent variable d. a categorical variable 9. The following regression model has been proposed to predict sales at a computer store....
HELP ASAP
Suppose you are wishing to fit a multiple linear regression model using one categorical variable that can take on 17 different values. For example, if you wished to use the months of the year in your model, the categorical variable "month" would have 12 different values: January, February, March, etc. In general, how many dummy variables would you need to incorporate into your model to completely capture the effect of all 17 conditions of a categorical variable on...
Decide (with short explanations) whether the following
statements are true or false.
e) In a simple linear regression model with explanatory variable x and outcome variable y, we have these summary statisties z-10, s/-3 sy-5 and у-20. For a new data point with x = 13, it is possible that the predicted value is y = 26. f A standard multiple regression model with continuous predictors and r2, a categorical predictor T with four values, an interaction between a and...
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