Homework Answers
This statement is True as in each step, we add or subtract an independent variable to check the effect on dependent variable.
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Answer the question True or False. Stepwise regression is used to determine which variables, from a...
Question 5 (1 point) The multiple regression model includes several dependent variables. True False Question 6...
Question 5 (1 point) The multiple regression model includes several dependent variables. True False Question 6 (1 point) Dummy variables for regression analysis can take on a value of either -1 or +1. True False Question 7 (1 point) The several criteria (maximax, maximin, equally likely, criterion of realism, minimax regret) used for decision making under uncertainty may lead to the choice of different alternatives. True False Question 8 (1 point)
Decide (with short explanations) whether the following statements are true or false. r) The error term in logistic regression has a binomial distribution s) The standard linear regression model (unde...
Decide (with short explanations) whether the following
statements are true or false.
r) The error term in logistic regression has a binomial distribution s) The standard linear regression model (under the assumption of normality) is not appropriate for modeling binomial response data t Backward and forward stepwise regression will generally provide different sets of selected variables when p, the number of predicting variables, is large. u) BIC penalizes for complexity of the model more than AIC
r) The error term...
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.
In multiple regression, the adjusted R2 controls for the number of dependent variables. True False
In multiple regression, the adjusted R2 controls for the number of dependent variables. True False
Part I: Determine whether each of the following statements is TRUE or FALSE, and write a...
Part I: Determine whether each of the following statements is TRUE or FALSE, and write a short explanation for your answer The mean and median are always equal to each other and can never be different. The median and mode must always be equal and can never be different. The expected value of a random variable is a weighted average of outcomes, where each outcome is weighted by its probability of occurrence. Regressions are used to estimate the relationship between...
QUESTION 1 The Simple Linear Regression is fit or constructed to predict a dependent variable. True...
QUESTION 1 The Simple Linear Regression is fit or constructed to predict a dependent variable. True False QUESTION 2 The Coefficient of Determination is used to explain in what percent (%) the independent variable is affecting the dependent variable. True False
11. Multiple regression analysis is used when one independent variable is used to predict values of...
11. Multiple regression analysis is used when one independent variable is used to predict values of two or more dependent variables. True or False 13. For a two-tailed null hypothesis, the test statistic Z=1.96. Therefore, the p-value is 0.05. True False
Please answer true / false / uncertain to the statement and EXPLAIN THE ANSWER. Measurement error...
Please answer true / false / uncertain to the statement and EXPLAIN THE ANSWER. Measurement error in the dependent variable has no effects on the results of a regression. It only matters when it is present in the explanatory variables.
4. True/False. You must justify your answer. If your regression suffers from imperfect multicollinearity, your estimated...
4. True/False. You must justify your answer. If your regression suffers from imperfect multicollinearity, your estimated coefficients will be biased We should always interpret the coefficient on a (non-dummy) control variable as the causal effect of changing the control variable by one unit of the dependent variable a. b.
Answer each question by writing TRUE or FALSE 1. For OLS estimators to be linear the...
Answer each question by writing TRUE or FALSE 1. For OLS estimators to be linear the explanatory variables must be variable, non- stochastic and fixed in repeated samples. Under the conditions of perfect multicollinearity, the OLS estimators are not unique. The presence of heteroskedasticity causes the OLS method to overestimate the variances 2. 3. of the parameters. The Breusch-Godfrey LM test is applicable when a lagged dependent variable is used. If we include a non-influential variable in an equation the...
Question 5 (1 point) The multiple regression model includes several dependent variables. True False Question 6 (1 point) Dummy variables for regression analysis can take on a value of either -1 or +1. True False Question 7 (1 point) The several criteria (maximax, maximin, equally likely, criterion of realism, minimax regret) used for decision making under uncertainty may lead to the choice of different alternatives. True False Question 8 (1 point)
Decide (with short explanations) whether the following
statements are true or false.
r) The error term in logistic regression has a binomial distribution s) The standard linear regression model (under the assumption of normality) is not appropriate for modeling binomial response data t Backward and forward stepwise regression will generally provide different sets of selected variables when p, the number of predicting variables, is large. u) BIC penalizes for complexity of the model more than AIC
r) The error term...
4. True/False. You must justify your answer. If your regression suffers from imperfect multicollinearity, your estimated coefficients will be biased We should always interpret the coefficient on a (non-dummy) control variable as the causal effect of changing the control variable by one unit of the dependent variable a. b.
Answer each question by writing TRUE or FALSE 1. For OLS estimators to be linear the explanatory variables must be variable, non- stochastic and fixed in repeated samples. Under the conditions of perfect multicollinearity, the OLS estimators are not unique. The presence of heteroskedasticity causes the OLS method to overestimate the variances 2. 3. of the parameters. The Breusch-Godfrey LM test is applicable when a lagged dependent variable is used. If we include a non-influential variable in an equation the...
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