Hi,

Please describe your data and write down your research hypothesis. By doing so, people can help you choose a suitable statistical test to test your hypothesis. Additionally, instead of reporting that 'Tenure is statistically significant,' it is better to say that 'statistically, the Tenure contribution in the model is not rejected at, let's say, a 0.05 significance level, given that the other variables are assumed to be in the model.'

I recommend taking a look at the following PDF: https://www.math.arizona.edu/~hzhang/waeso/multlr.pdf. It contains valuable information on multiple linear regression analysis.

Moreover, I suggest reading the chapter on 'partial F-test' in the book 'Introduction to Linear Regression Analysis' by D. Montgomery.

Good luck with your research!

Best regards,

Hamid

Thank you Hammid. I will follow your suggestion!

Hello Alejandrina,

In model 1, you establish that there is a non-zero relationship between scores on your measure of career development opportunities (CDO) and the DV of job satisfaction (JS).

In model 2, you similarly observe a non-zero relationship between CDO and JS, when your measure of Tenure and your measure for Sex are included. In fact, the (unstandardized) regression coefficient for CDO is pretty much the same in the unadjusted (model 1) and adjusted (model 2) results. What model 2 tells you beyond this is that T contributes significantly to the model, whereas Sex does not.

It's your task to explain the functional and theoretical implications of these results relative to the target population and the specific measures used.

Good luck with your work.

Thank you David!!