 When you suspect there may be an interaction between variables and a multiple regression you need to add a another variable an interaction variable to Take care of that or to help us find out if it's really a problem Here I'm going to add a variable age times mba and that's simply equal age Multiply times the mba dummy variable status, and then I'm going to copy that All the way down my column there So that's my third variable and now I'm going to go to data data analysis regression and here I need to Put my y-range which is again as my salary including the label at the top and then my X variables now I've got three and I select all three of those copy that range in That labels everything else default, and I want to put it up here in G3 and click okay, and I get results I'm going to expand those so we can see We've got our r square and adjusted r square and if we look down here this again, I'm going to format everything as decimals you can see Down in the lower part of the ANOVA that the mba term is Not significant when we include the interaction between age and mba so what we need to do is Run this again. We will not use the mba variable this time and just use age and the age times mba interaction variable Here I've copied the data over into another worksheet and Deleted the column of just the mba if you remember Broom regressions we have to have our x variables and adjacent columns So I had to eliminate that middle column since I didn't want it in there. We go back to data data analysis regression and I'm going to clean out again select salary for my response variable clean out Those values this time just age and age times mba For my predictor variables leave everything else the same except I want to change that location and put it back in F2 and click okay and We've got results again. I'm gonna select those and expand them so we can see everything here and again, I want to Format those p-values You can see this time both the age and the age times mba Slopes are Significant and again because of the type of work we're doing here We don't worry about the intercept being shown as not significant and the overall ANOVA is significant so we would use this equation to Predict our values of salary given age and mba step. I've added a table similar to the one that I showed you in the categorical variable video here We're looking at the variables age mba and salary and we're going to know the The value of the mba and to calculate it this empty cell there which is equal the intercept plus the age slope times age plus the age times mba slope and we need to multiply it times age times mba and that gives us a value of 58,340 for a 40 year old with an mba you can see the 50 year old same equation with an mba is at 72,000 and the difference Between having an mba and not having an mba Dippers as your age changes you can see it's $16,000 for a 40 year old and $20,000 plus for a 50 year old, so that's the impact of an interaction