You have to use k-1 dummy variables. Thus, 11 dummies.

When all the dummies are equal to zero you obtain January, when D1 is equal to 1 you get February, when D2 is equal to 1 (and the others zero) you have March.... and so on.

Thanks Fabrizio Maturo, I was Really confused all the night, trying to figure this out. But your insight made it more clearer now. Thank you so much. 

Hello Fabrizio maturo , Thanks for the other day.. Today i am dead stock now. I have few hours to deadline of submission and i need to come with reasoneable solution to this question. You got an idea ?? 

8: You have 7 years of monthly data and want to control for seasonality by adding dummy variables for the month-of-year. How many dummy variables should you add to the regression?

Q9: After estimating the Q8 regression, you observe that the coefficient of your first dummy is not significantly different from zero. What does that mean? What can/should you do next?

Q1: What is the difference between the sales effect and the sales elasticity of a marketing action? Which one is most interesting to the marketing manager? To the marketing academic?

Q2: Three popular functional forms are linear, semilog, and multiplicative model. What is the underlying idea/theory about customer response that justifies each model? How does the resulting elasticity look like for each model?

First, I think that 11 dummy are too many, I would prefer to control for 4 seasons (winter, summer, ecc.. using 3 dummies).

However, if you use 11 dummies for 12 months.... decide if the month without "direct" dummy is the first or the last.... let's suppose it is the first.

Thus, the first dummy D1 is 1 if you observe February and 0 if it is not February.... and so on.

If D1 is significant it means that february is statistically different from Juanuary.

I can not answer to Q1 and Q2 because I do know marketing.