1. Consider the following sales figures for the past five years. Year 1 2 3 4 5 Sales 135 142 150 145 160 (a) Use simple average to forecast sales for this year (year 6). (b) Use moving average with n = 2 to forecast sales for this year. (c) Use exponential smoothing with a = 0.1 and an initial forecast value of 150 to forecast sales for this year.

Consider the following data: Month Jan-14 Feb-14 Profit ($) 16,113 16,263 Monthly Profit of an Auto Repair Shop Mar-14 Apr-14 May-14 Jun-14 Jul-14 Aug-14 Sep-14 15,055 17,117 18,763 17,210 19,141 18,468 20,254 Step 3 of 4: Determine the exponential smoothing forecast for the next time period using a smoothing constant of 0.35. If necessary, round your answer to one decimal place.

Describe the patterns in quantity sold and own and rival prices during this time period using basic descriptive statistics.  Graphs are welcome as well. Take the logs of the variables, and estimate the demand function. Interpret the R-square. Interpret the coefficients for logP and logPsub Interpret the p-values associated with each independent variable Are consumers price sensitive? Why or why not?  (be as precise as you can – you have estimates!). Does this price sensitivity make sense given the good we are examining? How sensitive are our consumers to changes in the rival good’s price? Explain in detail. Suppose we decide to charge a per ounce price of $2, while at the same time our rival charges a price of $2.15. All else equal, what would you expect sales to be?  How confident are you in your forecast?  Suppose we are charging a price of $2 and our current marginal cost is $1.50 Are we maximizing profits at this price?  If not, should we raise or lower price?  Why?

The following table contains the demand from the last 10 months: MONTH ACTUAL DEMAND 1 31 2 34 3 33 4 35 5 37 6 36 7 38 8 40 9 40 10 41 a. Calculate the single exponential smoothing forecast for these data using an α of 0.30 and an initial forecast ( F1�1 ) of 31. Note: Round your intermediate calculations and answers to 2 decimal places.   b. Calculate the exponential smoothing with trend forecast for these data using an α of 0.30, a δ of 0.30, an initial trend forecast ( T1�1 ) of 1, and an initial exponentially smoothed forecast ( F1�1 ) of 30. Note: Round your intermediate calculations and answers to 2 decimal places.   c-1. Calculate the mean absolute deviation (MAD) for the last nine months of forecasts. Note: Round your intermediate calculations and answers to 2 decimal places.   c-2. Which is best? multiple choice Exponential smoothing with trend forecast Single exponential smoothing forecast