(I AM A MAC USER)

The Excel file contains data on sports club memberships and sports club features (swimming pool, racquetball courts, and fitness classes) for 16 sports clubs in the franchise. There is also the median income for the neighborhoods in the vicinity of the sports clubs. The data analysis should address the number of members as a function of the other variables. Make recommendations on what features new builds should contain to drive membership numbers for the sports clubs.

Task: Build and justify the best multiple linear regression model possible from the variables given.

-Introduce the task including variables and their units.

-Include graphs of the independent variables against the dependent variable, a correlation matrix to argue the inclusion/exclusion of variables in the model, the R² values, the standard errors, the coefficients of the model (with their units), the significance of the coefficients (p-values), and/or any other type of analysis we have covered in the first five weeks of the course.

-Would a quadratic model fit the data better?

-Explain how you determined that your model is the best one for the data set given. What should we do with this model? What conclusions about the variables can be made?

-Any recommendations as to who to market to?

-Any recommendations on where to locate new sports clubs?

-Could any other variables be monitored that might make the model better?

NumberOfMembers Medianlncome($) 1480 2615 3765 4393 4787 1258 1479 1701 2014 2271 2632 2737 2810 3563 3792 4069 mmmmmmmmmmmmmmmm 43,187.00 58,347.00 81,289.00 86,885.00 88,381.00 32,223.00 34,975.00 44,337.00 52,167.00 _ 57,521.00 60,960.00 62,201.00 67,993.00 68,770.00 83,902.00 84,594.00 Pool? RacquetballCourts? FitnessClasses? no no yes yes yes no no no no no yes yes no no no yes yes yes yes yes yes no no no no no no no no no no no no no yes yes yes no no no yes yes no yes yes yes yes yes