Making sense of result parameters
Apart from the R2 statistic, there are other statistics and parameters that one needs to look at in order to do the following:
Select some variables and discard others for the model.
Assess the relationship between the predictor and output variable and check whether a predictor variable is significant in the model or not.
Calculate the error in the values predicted by the selected model.
Let us now see some of the statistics which helps to address the issues discussed earlier.
p-values
One thing to realize here is that the calculation of a and β are estimates and not the exact calculations. Whether their values are significant or not need to be tested using a hypothesis test.
The hypothesis tests whether the value of β is non-zero or not; in other words whether there is a sufficient correlation between X and yact. If there is, the β will be non-zero.
In the equation, y= a +β*x, if we put β=0, there will be no relation between y and x. Hence the hypothesis test is...
