Which statements are incorrect? In a regression model. If variance of the dependent variable, y conditional on an explan

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Which Statements Are Incorrect In A Regression Model If Variance Of The Dependent Variable Y Conditional On An Explan 1 (43.98 KiB) Viewed 35 times

Which statements are incorrect? In a regression model. If variance of the dependent variable, y conditional on an explanatory variable, X, or artylx), is not constant, the t statistics and the confidence intervals are both Invalid no matter how large the sample size is. For a given significance level of the calculated value of the Durbin Watson statistic lles between the lower critical value and the upper critical value, the hypothesis of no serial correlation is accepted. The variance of the slope estimator decreases as the error variance decreases. In time series regressions, it is advisable to check for heteroskedasticity first, before checking for serial correlation ce stationarity focuses only on the first two moments of a stochastic process. agression model contains homoskedasticity of the Breusch-Pagan test results in a large p-value. A variable is standardized in the sample by subtracting off its mean and multiplying by its standard deviation Whenever there is strong heteroskedasticity, it is preferable to use ordinary least square rather than Weighted least square, which may use a possibly misspecified variance function. The homoskedasticity assumption in time series regression suggests that the variance of the error term cannot be a function of time.