Starbucks Case

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1. The null hypothesis: There are no promising variables that seem to have a relationship with the amount of the prepaid cards

The alternative hypothesis: There are variables that have a relationship to the amount stored on the prepaid card.

To find out of if we are to accept or reject the null hypothesis we are first to determine the critical value, this was done by using the denominators (20), and then aligning with the number of degrees of freedom (4) at the 0.05 significance level. The F-Critical value was determined to be 5.80. the F-value is 15.3782. When the F-stat is greater than the F-value then we reject the null hypothesis. This indicates that there is in fact an existing relationship with the amount on the prepaid cards along with other independent variables.

Data indicates that the independent variable that has the strongest relationship with the dependent variable is the income of the prepaid card holder. The T-stat is greater than T-critical value, and as a result the P-value is less than the alpha. After an analysis of the regression, it would be valuable for Starbucks to place emphasis on the sales of prepaid debit cards in regions where a higher income has been documented.

2. The Null Hypothesis: There is no relationship with the number of days spent in starbucks per month (dependent variable), with age, income, prepaid balance, cups of coffee (independent variables)

The Alternative Hyphothesis: There is a relationship with the number of days spent in starbucks per month with the independent variables.

Data indicates that the p-value of (0.0066) is less than the alpha for the number of cups of coffee per day, this means we reject the null hypothesis, and accept that there is in fact a relationship of significance between the number of days per month in a starbucks and the number of cups consumed in a day. The data indicates that the other independent variables are greater than the alpha thereby accepting the null in that...
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