Reference no: EM13902675

1. Using the data below., develop a multiple regression model to predict score (rating) based on restaurant type (0 = Italian and 1 = Seafood/Steakhouse) and price of a meal in dollars. Be sure to include a correlation matrix along with your excel solution. (attach or email) Next answer the following questions: 1.Write the regression equation, 2. Interpret the regression constant and partial regression coefficients, 3. Forecast a value for the dependent variable using the regression model, 4. Test the significant of the partial regression coefficients at an alpha level of .05, 5. Test the overall significant of the regression model, 6. Interpret the adjusted coefficient of determination, and 7. Are there any indications of multicollinearity, be very specific.

Type     Price     Score

   0            16        77

   1            24        79

   1            26        85

   0            18        84

   0            17        81

   1            18        77

   0            23        86

   1            17        75

   0            28        83

   1            15        71

   0            17        81

   1            17        76

   1            19        81

   0            22        83

   1            16        81

   0            19        81

   1             20       80

   1             18       78

   0             18       82

   0             12       79

   0             16       76

2. Using the data below develop an x bar chart and an R chart. Be sure to include the chart. After developing the charts comment on whether they are statistically in control or not.

Cattlemen's Bar and Grill The Cattlemen's Bar and Grill in Kansas city, Missouri, has developed a name for its excellent food and service. To maintain this reputation, the owners have established key measures of product and service quality , and they monitor them regularly. One measure is the amount of time customers wait from the time they are seated until they are served.

Every day, each hour that the business is open, four tables are randomly selected. the elapsed time from when the customers are seated at these tables until their orders arrives is recorded. The resulting data is shown below.

Hour   Table 1    Table 2     Table 3    Table 4

   1          16           18             21            23

   2          26           20             19            19

   3          20           22             18            18

   4          24           16             22            20

   5          17           19             24            17

   6          17           17             15            18

   7          22           12             20            22

   8          24           19             19            17

   9          18           18             20            14