I am working on a multiple regression model that will forecast the value of loans being granted within the current month.
The data points are broken down per day ( Jan will have 31 data points etc) and I will be updating the model every week.
I have 4 independent variables driving the model. I am currently testing the model and trying to understand what is happening in particular to the $p$-values.
On Day 8, 2 of my Variables (loans and declines) have $p$-values of
loans 0.014030324 declines 0.980464984
On day 15 when I run the regression I get these
loans 0.003114471 declines 0.023498327
I am just wondering why the "declines" $p$-value is now starting to show as a significant value. Is it because the model is working over more data points or is there something in the data that is suggesting that this variable is becoming more significant?