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If durbin Watson statistic less than 1 then positive serial correlation is likely an issue
Because,
The Durbin-Watson statistic will always have a value between 0 and 4. A value of 2.0 means that there is no autocorrelation detected in the sample. Values from 0 to less than 2 indicate positive autocorrelation and values from from 2 to 4 indicate negative autocorrelation.
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Question 11 3 pts If the Durbin-Watson statistic is less than 1, then negative serial correlation...
If the Durbin-Watson statistic is greater than 3, then Group of answer choices positive serial correlation...
If the Durbin-Watson statistic is greater than 3, then
Group of answer choices
positive serial correlation is likely an issue.
non-stationarity is likely an issue.
negative serial correlation is likely an issue.
spurious regression is likely an issue.
Suppose you estimate a multiple regression model using OLS and
the coefficient of determination is very high (above 0.8), while
none of the estimated coefficients are (individually) statistically
different from zero at the 5-percent level of significance. The
most likely reason for...
Question 11 If the Durbin-Watson statistic is less than 1, then O non-stationarity is likely an...
Question 11 If the Durbin-Watson statistic is less than 1, then O non-stationarity is likely an issue. O positive serial correlation is likely an issue. O spurious regression is likely an issue. negative serial correlation is likely an issue. Question 12
If the Durbin-Watson statistic is greater than 3, then: spurious regression is likely an issue. non-stationarity...
If the Durbin-Watson statistic is greater than 3, then: spurious regression is likely an issue. non-stationarity is likely an issue. negative serial correlation is likely an issue. positive serial correlation is likely an issue.
Please answer the following questions, thannks plzz Question 11 3 pts If the Durbin-Watson statistic is...
Please answer the following questions, thannks plzz
Question 11 3 pts If the Durbin-Watson statistic is less than 1, then o negative serial correlation is likely an issue. spurious regression is likely an issue. O positive serial correlation is likely an issue. O non-stationarity is likely an issue. Question 12 3 pts Consider the estimated multiple regression model using OLS, with the standard errors in parentheses below each estimated coefficient. There are 1,576 observations in the sample: Y; = 10...
Question 10 3 pts Which of the following would result in the widest (largest) confidence interval?...
Question 10 3 pts Which of the following would result in the widest (largest) confidence interval? o large sample size and 99-percent confidence o large sample size and 95-percent confidence o small sample size and 99-percent confidence small sample size and 95-percent confidence. Question 11 3 pts If the Durbin-Watson statistic is less than 1, then spurious regression is likely an issue. o positive serial correlation is likely an issue. o non-stationarity is likely an issue. o negative serial correlation...
Question 7 3 pts Suppose that you have 50 observations on the variables Y and X....
Question 7 3 pts Suppose that you have 50 observations on the variables Y and X. If the sample correlation coefficient is 0.5 (r=0.5), and you want to test the null hypothesis that the true population correlation coefficient (rho) is equal to zero, then the test statistic associated with this null hypothesis is: o 5 04 O2 O 3 Question 8 3 pts Suppose you estimate a multiple regression model using OLS and the coefficient of determination is very high...
Serial correlation, its implications on the OLS model. What is classical Assumption 4 Error term has...
Serial correlation, its implications on the OLS model. What is classical Assumption 4 Error term has constant variance Error term is normally distributed All explanatory variables are un correlated with error term Different observations of error term are uncorrelated each other Relationship between serial correlation and classical assumption 4. Serial violates classical assumption 4 always hold Serial violates support Serial violates is not related Serial violates is used to help when 4 violated Assuming we are using an appropriate test...
Question 8 3 pts Suppose you estimate a multiple regression model using OLS and the coefficient...
Question 8 3 pts Suppose you estimate a multiple regression model using OLS and the coefficient of determination is very high (above 0.8), while none of the estimated coefficients are (individually) statistically different from zero at the 5-percent level of significance. The most likely reason for this result is: O multicollinearity. omitted variable bias. O serial correlation. spurious regression. 3 pts Question 9
Question 8 3 pts Suppose you estimate a multiple regression model using OLS and the coefficient...
Question 8 3 pts Suppose you estimate a multiple regression model using OLS and the coefficient of determination is very high (above 0.8), while none of the estimated coefficients are (individually) statistically different from zero at the 5-percent level of significance. The most likely reason for this result is: omitted variable bias. o serial correlation. spurious regression. o multicollinearity.
Question 8 3 pts Suppose you estimate a multiple regression model using OLS and the coefficient...
Question 8 3 pts Suppose you estimate a multiple regression model using OLS and the coefficient of determination is very high (above 0.8), while none of the estimated coefficients are (individually) statistically different from zero at the 5-percent level of significance. The most likely reason for this result is: spurious regression. omitted variable bias. multicollinearity. serial correlation.
If the Durbin-Watson statistic is greater than 3, then
Group of answer choices
positive serial correlation is likely an issue.
non-stationarity is likely an issue.
negative serial correlation is likely an issue.
spurious regression is likely an issue.
Suppose you estimate a multiple regression model using OLS and
the coefficient of determination is very high (above 0.8), while
none of the estimated coefficients are (individually) statistically
different from zero at the 5-percent level of significance. The
most likely reason for...
Question 11 If the Durbin-Watson statistic is less than 1, then O non-stationarity is likely an issue. O positive serial correlation is likely an issue. O spurious regression is likely an issue. negative serial correlation is likely an issue. Question 12
Please answer the following questions, thannks plzz
Question 11 3 pts If the Durbin-Watson statistic is less than 1, then o negative serial correlation is likely an issue. spurious regression is likely an issue. O positive serial correlation is likely an issue. O non-stationarity is likely an issue. Question 12 3 pts Consider the estimated multiple regression model using OLS, with the standard errors in parentheses below each estimated coefficient. There are 1,576 observations in the sample: Y; = 10...
Question 10 3 pts Which of the following would result in the widest (largest) confidence interval? o large sample size and 99-percent confidence o large sample size and 95-percent confidence o small sample size and 99-percent confidence small sample size and 95-percent confidence. Question 11 3 pts If the Durbin-Watson statistic is less than 1, then spurious regression is likely an issue. o positive serial correlation is likely an issue. o non-stationarity is likely an issue. o negative serial correlation...
Question 7 3 pts Suppose that you have 50 observations on the variables Y and X. If the sample correlation coefficient is 0.5 (r=0.5), and you want to test the null hypothesis that the true population correlation coefficient (rho) is equal to zero, then the test statistic associated with this null hypothesis is: o 5 04 O2 O 3 Question 8 3 pts Suppose you estimate a multiple regression model using OLS and the coefficient of determination is very high...
Question 8 3 pts Suppose you estimate a multiple regression model using OLS and the coefficient of determination is very high (above 0.8), while none of the estimated coefficients are (individually) statistically different from zero at the 5-percent level of significance. The most likely reason for this result is: O multicollinearity. omitted variable bias. O serial correlation. spurious regression. 3 pts Question 9
Question 8 3 pts Suppose you estimate a multiple regression model using OLS and the coefficient of determination is very high (above 0.8), while none of the estimated coefficients are (individually) statistically different from zero at the 5-percent level of significance. The most likely reason for this result is: omitted variable bias. o serial correlation. spurious regression. o multicollinearity.
Question 8 3 pts Suppose you estimate a multiple regression model using OLS and the coefficient of determination is very high (above 0.8), while none of the estimated coefficients are (individually) statistically different from zero at the 5-percent level of significance. The most likely reason for this result is: spurious regression. omitted variable bias. multicollinearity. serial correlation.
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