Scenario 2
Use the scenario described below to answer the following questions.
You oversee pricing for a California wine company. Because nearly 90% of U.S. wines are produced in California, you think that California wines might be perceived differently from those produced in other states, thus affecting the price. You decide to see how both wine rating and whether the wine is from California affect the pricing of wines in the U.S.
For this question, you will need to download the Wine Rating Data – Dummy Variables and then use the data analysis tool pack in Excel to run a regression. Note that for the dummy variable, you will need to use an IF command to make that column.
Based on the Excel output, which of the variables would be included in the best model for predicting wine price with a 5% significance level and why?
All the variables should be included because we have a very large F test statistic and a very small Significance F (p-value).
None of the variables should be included because they each have p-values less than 0.05.
All the variables should be included because they each have p-values less than 0.05.
Only Rating because it is the only statistically significant variable.
Only Rating and California because we reject the null when performing a test of joint significance (F-test).