1. TYPE or PASTE your answers in the indicated area (submit as a WORD file).
2. This is an individual assignment, to be completed by you on your own.
Questions #1 through #11: Suppose Sally Fry collects burger sales for a new year (i.e., different from the year’s worth of data that we analyzed in class), recording again burger sales every single day of the new year. The file containing this data is found on Blackboard, in the foodtrucktwo.sav file.
Use the foodtrucktwo.sav to answer Questions #1 through #11 below. Assume the same food costs (Ex. 1), parking costs (case text), and travel distances (Ex. 2) as contained in the original Food Truck Forecaster case. Now, however, assume that Sally’s truck gets 6 kilometers per liter, and that the price of gas is 106.8 cents per liter.
1. What is the correlation between the number of burgers sold and price?
Answer: _____-.172 _________ (to 2 decimal places)
2. Run a regression model that predicts the number of burgers sold (i.e., QSold) as a function of the independent variables available in the data set (variable names provided below; variable definitions are the same as in the original case). Provide the SPSS output below, showing the regression coefficients.
(Note: some variables in the data file may include extra decimal-level precision, e.g., the values for QSold (to account for spoilage). That’s OK – just run the regression model using the values in the data set as they are entered).