When two explanatory variables are highly correlated, should you remove one of the correlated explanatory variables to reduce the multicollinearity problem.
A. Yes, it will reduce the standard errors on the coefficients and increase the t statistics.
B. No, it will not affect the t statistics on the coefficients.
C. No, it will cause the coefficient on the remaining variable to be biased.
D. Yes, it will improve the fit of the regression model.
The correct option is A.)Yes, it will reduce the standard errors on the coefficients and increase the t statistics.
When two explanatory variables are highly correlated, should you remove one of the correlated explanatory variables to reduce the multicollinearity problem.
A.) Yes, it will reduce the standard errors on the coefficients and increase the t statistics.
When two explanatory variables are highly correlated, should you remove one of the correlated explanatory variables...
Suppose that you estimate a multiple regression model, but that you inadvertently omit an explanatory variable that is correlated with the dependent variable. In this case, the coefficients on the included variables will always be unbiased, but the standard errors and test statistics will be biased. the coefficients on the included variables will always be biased. there is no effect on the coefficients of the included variables since the omitted variable has been omitted. the coefficients on the included variables...
Question 14 3 pts Suppose that you estimate a multiple regression model, but that you inadvertently omit an explanatory variable that is correlated with the dependent variable. In this case, the coefficients on the included variables will always be unbiased, but the standard errors and test statistics will be biased. there is no effect on the coefficients of the included variables since the omitted variable has been omitted. the coefficients on the included variables will always be biased. the coefficients...
Multicollinearity occurs when... Select one: independent variables are perfectly correlated dependent variables are perfectly correlated an independent variable is perfectly correlated with the dependent variable the error term is perfectly correlated with the intercept All/Any of the above. Which of the following statements is true regarding an F-Test? Select one: It is a joint hypothesis test. The null hypothesis states the all slope coefficients in the population regresion model are equal to zero. It tests whether or not one's regression...
Question 14 3 pts Suppose that you estimate a multiple regression model, but that you inadvertently omit an explanatory variable that is correlated with the dependent variable. In this case, the coefficients on the included variables will always be biased. the coefficients on the included variables will always be unbiased, but the standard errors and test statistics will be biased. there is no effect on the coefficients of the included variables since the omitted variable has been omitted. the coefficients...
Can someone please help solve this, its econ with stats
Question 14 3 pts Suppose that you estimate a multiple regression model, but that you inadvertently omit an explanatory variable that is correlated with the dependent variable. In this case, O the coefficients on the included variables will be unbiased if the included variables are not correlated with the omitted variable. O the coefficients on the included variables will always be biased. Othere is no effect on the coefficients of...
Use the following linear regression equation to answer the questions. x1 = 1.5 + 3.4x2 – 8.3x3 + 2.3x4 (a) Which variable is the response variable? Which variables are the explanatory variables? (b) Which number is the constant term? List the coefficients with their corresponding explanatory variables. constant? x2 coefficient? x3 coefficient? x4 coefficient? (c) If x2 = 1, x3 = 8, and x4 = 6, what is the predicted value for x1? (Use 1 decimal place.) (d) Explain how...
A linear regression of a variable Y against the explanatory variables X1 and X2 produced the following estimation model: Y = 1615.495 + 9.957 X1 + 0.081 X2 + e (527.96) (6.32) (0.024) The number in parentheses are the standard errors of each coefficients i. State the null and alternative hypothesis for the coefficients Select the appropriate test, compute the test statistic based on the information above, and test the null hypothesis for each coefficient by using a level of...
Question 13 3 pts Consider three data series, each a random sample of seven observations (n = 7): Series 1: {1, 1, 1, 3, 5, 5, 5} Series 2: {1, 1, 3, 3, 3, 5, 5} Series 3: {1, 3, 3, 3, 3, 3, 5} The interquartile range of Series 3 is: 4 0 3 2 Question 14 3 pts Suppose that you estimate a multiple regression model, but that you inadvertently omit an explanatory variable that is correlated with...
Need help with stats true or false questions
Decide (with short explanations) whether the following statements are true or false a) We consider the model y-Ao +A(z) +E. Let (-0.01, 1.5) be a 95% confidence interval for A In this case, a t-test with significance level 1% rejects the null hypothesis Ho : A-0 against a two sided alternative. b) Complicated models with a lot of parameters are better for prediction then simple models with just a few parameters c)...
The data in the accompanying table give the prices (in dollars) for gold link chains at the Web site of a discount jeweler. The data include the length of the chain (in inches) and its width (in millimeters). All of the chains are 14-carat gold in a similar link style. Use the price as the response. For one explanatory variable, use the width of the chain. For the second, calculate the "volume" of the chain as π times its length...