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Simple guide on how to White Out test 2

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How to White Out test 2

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What is the p-value of White test?

From Whites test (analytical method), we decided to reject the null hypothesis of homoscedasticity in the model as the p-value obtained is 004256. This is because the p-value is defined as the minimum value of significance from which the null hypothesis is rejected.

What is the White test for heteroskedasticity?

Whites test is a statistical test that determines whether the variance of the residuals in a regression model is constant. The null hypothesis states that 1 = 2 = 0 (homoskedasticity). The test statistic is defined as: LM = nR2 where R2 is the R-squared value from the regression of u2.

What does the White test tell us?

In statistics, the White test is a statistical test that establishes whether the variance of the errors in a regression model is constant: that is for homoskedasticity. This test, and an estimator for heteroscedasticity-consistent standard errors, were proposed by Halbert White in 1980.

What is the formula for Whites test?

A graph showing heteroscedasticity; the White test is used to identify heteroscedastic errors in regression analysis. The null hypothesis for Whites test is that the variances for the errors are equal. In math terms, thats: H0 = 2i = 2.

What is whiteness test criteria?

ing to the whiteness test criteria, a good model has the residual autocorrelation function inside the confidence interval of the corresponding estimates, indicating that the residuals are uncorrelated. ing to the independence test criteria, a good model has residuals uncorrelated with past inputs.

How do you perform a whites test?

Whites Test for Heteroscedasticity Run the desired linear regression model, saving the (unstandardized) residuals. Square the saved residuals. Compute squared values of all predictors and products of all pairs of predictors.

What is the critical value for White test?

The Critical value is 5 2 at 5% level of significance is 11.07. Since the calculated value is smaller than the tabulated value, therefore, the null hypothesis is accepted. Therefore, on the basis of the White general heteroscedasticity test, there is no heteroscedasticity.

What does the White test test for?

In statistics, the White test is a statistical test that establishes whether the variance of the errors in a regression model is constant: that is for homoskedasticity. This test, and an estimator for heteroscedasticity-consistent standard errors, were proposed by Halbert White in 1980.

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White Out test 2