# Dummy Data & Regression Analysis

I've been doing some analysis projects at work and I've been supplied with some dummy data regarding whether an applicant has applied on a weekday or weekend (I have set this as 0 for weekend and 1 for weekday. The other variable I have is the total time it took for an applicant to apply and get recruited.

Now from a statistical stand-point if I use a regression analysis against this dummy data and I receive a P value < 0.05 - can I say safely say that there exists a linear regression relationship and that the day the individual applies has an impact on overall recruitment? Of course the upper and lower ranges are also +ve as well as an adjusted R squared of 0.70.

To verify the relevance of this variable I was thinking of using a multiple regression analysis to test for the P-values and see whether there is an associated increase with any other variables (to test for mutlicollinearity).

The regression analysis you are using in this case is equivalent to the independent samples $t$-test (assuming the same applicant doesn't appear in the dataset multiple times). You can verify this by running the regression analysis and then a $t$-test between the two groups and examining the resulting $p$-values. They will be identical. Your analysis says that there is a statistically significant difference in the total time it took for an applicant to apply and get recruited between those who apply on the weekend and those who apply on weekdays. In other words there is as association between weekend/weekday applicants and an increase/decrease in total recruitment time.
Whether or not it is actually the weekend/weekday that is driving/causing the difference in total time is an entirely different question. You will likely need to control for a whole host of other factors to gain a better understanding of what may actually be $causing$ the differences.