What if Ljung-Box test is significant?
The null hypothesis of the Box Ljung Test, H0, is that our model does not show lack of fit (or in simple terms—the model is just fine). The alternate hypothesis, Ha, is just that the model does show a lack of fit. A significant p-value in this test rejects the null hypothesis that the time series isn’t autocorrelated.
What is the p-value of the appropriate hypothesis test?
P Value vs Alpha level When you run the hypothesis test, the test will give you a value for p. A small p (≤ 0.05), reject the null hypothesis. This is strong evidence that the null hypothesis is invalid. A large p (> 0.05) means the alternate hypothesis is weak, so you do not reject the null.
What’s the p value for the Ljung Box test?
In general, what is important here is to keep in mind that p-value < 0.05 lets you reject of the null-hypothesis, but a p-value > 0.05 does not let you confirm the null-hypothesis. In particular, you can not proof the independence of the values of Time Series using the Ljung-Box test.
When to reject the null hypothesis in Ljung-Box test?
In this particular case the Ljung-Box test tries to reject the independence of some values. What does it mean? If p-value < 0.051: You can reject the null hypothesis assuming a 5% chance of making a mistake.
How to test the white noise hypothesis in Excel?
The summary statistics and tests: The P-Value of the Ljung-Box white noise test (white test in Excel) is greater than significance level (i.e. α ), so we don’t reject the white noise hypothesis ( Ho ), or, simply stated; there is no statistical evidence of a serial correlation, so the data can be white noise.
What does a p-value <.05 mean?
A small p-value (for instance, p-value < .05) indicates the possibility of non-zero autocorrelation within the first m lags. Below there is Minitab output for the Lake Erie level data that was used for homework 1 and in Lesson 3.1.