Things I learned from today’s lecture.
- P-Value:- It is the probability of obtaining the results while performing hypothesis tests. It assumes that the null hypothesis is correct.
2. If the P-value is less than 0.05 it indicates stronger proof against the given statement and if the P-value is greater than 0.05 it indicates weaker proof against the given statement.
3. Heteroscedasticity:- In heteroscedasticity the variance of the residual term, varies widely.
4. R-square:- It defines the variance in our data. If it is high, the prediction of the model is good.