Hypothesis Testing, P-value, Breusch-Pagan Test
Today’s lecture was focused on Hypothesis Testing, what’s P-value? And Breusch-Pagan Test.
Hypothesis Testing is a statistical method, where it’s a quantitative statement about population based on the sample data. There’re two hypothesis available Null Hypothesis and Alternative Hypothesis.
Null Hypothesis: It’s a claim or statement about population parameter that is assumed to be true until it’s declared to be false. It’s notation is H0. This null hypothesis could be rejected and only accepted after few tests.
Alternative Hypothesis: Any hypothesis which is complementary to null hypothesis. In this alternative hypothesis test there would be a difference between the two variables which is accepted iff we reject H0(Null Hypothesis). It is also known as a Research Hypothesis.
P-value it is the probability for the “Null hypothesis” to be true or it’s the probability value of obtaining results at least as extreme as observed results in a null hypothesis is true. This tells the probable occurrence of that data value in the null hypothesis. The P-value ranges between 0 and 1. There’s a P-value=0.05, which is known as Significance value. If my experiment comes up with a value and if value falls under extreme region values then we’ll reject null hypothesis saying that the experiment value is a away from the mean value. These significance values are derived by the domain experts which can be varied. Based on P-value we can also derive how much standard deviation will be away from the mean by using the z-test or t-test.
Breusch-Pagan test aids to detect the heteroscedasticity in the regression model with independent variables along squared residuals. For this if the P-value is less than Significant value, we come for closure saying as heteroscedasticity exists in this regression model.