1.) Given the data set in the Excel spreadsheet,write the theoretical demand equation using the appropriate variable names.These variable names must be very short and in capital letters.For example,QTY for Y,PRPIZZA for X1,PRDRK for X3. For example,if you used QTY for quantity,use QTY in the estimating demand equation (in your estimated regression model) rather than Y.Use the exact variable name you used in the data.
Do not use Y and X1,X2,X3 and so on.
2.)After estimating the pizza demand,write the estimated demand equation.Make sure you use the estimated coefficients you obtained from the regression output.
3.) Is the estimated coefficient of the price for pizza statistically significant at the 5% level? You can use either the p test or the p value.What does it mean when you reject the null hypothesis?
4.) Compute the price elasticity of demand.When computing the price elasticity of demand use the average price elasticity of demand.
5.) What is the adjusted R square?Explain the meaning of the the number of the R squared that you got.
My name is Leonardos and I am more than happy to help you with this.
1.) You can use initials of the titles of the variables or abbreviations, but make sure that whatever you use is easy to understand by someone who sees this regression for the first time.
3.) In order to determine the statistical significance of the estimated coefficient of the price of pizzas at the 5% level, you have to do the following:
a.) Set up your hypothesis and determine whether it's a one tailed or two tailed test.
b.) Draw the probability ...
This solution is an explanation of what you have to do in order to model and evaluate a demand regression equation.
Here you will find the use of various tests in order to evaluate your regression model as well as an explanation of price elasticity.