Question

This problem focuses on a very profitable product that our company sells - the Tiger ONE widget or T1 for short. You have been asked to provide input on the ordering policy currently being used for the Ti. Part 1 - Demand Sales and marketing tracks actual weekly sales but report these sales by rounding to the nearest 1,000 units sold. For modeling purposes, we are assuming that the errors associated with rounding are not large enough to be of concern. The table below displays the sales volume and the number of weeks in the past year that each volume was realized. You can assume that nothing extraordinary was done to influence these numbers (e.g., sales promotions) so variability is due to natural market fluctuations. Weekly sales volume 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000 Number of weeks this sales volume occurred in the past year 6 4 7 8 9 6 4 1 3 4 1. Convert this data into a probability distribution. This will be used as our best estimate of the probability that each of these demands will occur in the future and used in calculations to help decision makers with deciding on an ordering policy.

Answer 1

This data is converted into a Probability Distribution as follows:

Weekly Sales Volume (x)	Proportion of weeks this Sales Volume occurred out of the Total number of weeks in the past year
1,000	6/52=0.1154
2,000	4/52=0.0769
3,000	7/52=0.1346
4,000	8/52=0.1538
5,000	9/52=0.1731
6,000	6/52=0.1154
7,000	4/52=0.0769
8,000	1/52=0.0192
9,000	3/52=0.0577
10,000	4/52=0.0769
Total	1.0000