Business Scenario Predicting Fuji Apple Purchases Review the monthly data involving Fuji apples purchased at a large grocery store. Predict how many Scenario 5 have available for the customers in December (month 12)? Topic 5 Month 1 2 3 4 5 6 7 8 9 10 11 Fuji Apples Purchased 5,325 5,648 5,873 9,842 8,234 9,421 10,123 9,784 10,443 9,564 10,147 Hint: When determining the solution to this question remember that am around holidays. Seasonality is a characteristic of a time series in which predictable changes that recur every calendar year. Any predictable cha recurs or repeats over a one-year period can be said to be seasonal. linear trend 12,000 10,000 f(x) = 502.3363636364x + 5568.1636363636 R = 0.6998173284 8,000 Fuji Apples Purchased 6,000 Fuji Apples Purc 4,000 2,000 0 2 4 6 8 10 12 Month I would consider the linear regression model as compared to the exponential mode higher as that of the exponential model. But the linear model seems to be more effi to interpret it. From the linear model, we can say that with a unit increase in a mon Fuji Apples Purchased. ario ery store. Predict how many Fuji apples will need to be in stock to question remember that amounts needed in a store will go up tic of a time series in which the data experiences regular and ar year. Any predictable change or pattern in a time series that n be said to be seasonal. exponential 12,000 f(x) = 5613.740466773 exp( 0.0659278285 x ) 10,000 R = 0.6934728868 8,000 Fuji Apples Purchased 6,000 4,000 2,000 0 2 4 6 8 10 Month d to the exponential model. The value of adjusted R^2 is slightly model seems to be more efficient with calculations and being able ith a unit increase in a month there is 502.34 units increase in 12