Multiipe regression equation query

Suppose I'm looking at frequency of domestic garden watering and through running a t-test have determined that there are two periods in time which differ significantly in garden watering frequency - spring/summer and autumn/winter. I've also run correlations and determined that the key predictor variables in both cases are temperature and socio-economic status of the household.

Now if I want to perform a multivariate regression to predict frequency of garden watering, do I need to create two regression equations, one for spring/summer and one for autumn/winter given that the t-test showed the distributions are different, or do I just create one regression equation for the whole year?

Thanks

-Rob

Re: Multiipe regression equation query

If i remember correctly you can either fit 2 seperate lines or a combined model as follows:

y = frequency

X1 = temperature

X2 = socio-economic class

X3 = Season indicator (0=spring/summer, 1=autumn/winter)

$\displaystyle y_i = a + b_1X_1 + b_2X_3X_1 + b_3X_2 + b_4X_3X_2 + b_5X3 +e_i$

This will give different slopes and intercepts for each value of the indicator variable. I dont remember, but i **suspect ** the two approaches give the same answer unless you can use some process to reduce the number of terms in the combined model.

Re: Multiipe regression equation query

Thanks (again) Spring. You're fast becoming my MHF Hero! :D