You are recruited by a European wholesaler of shopper merchandise to improve their estimating capacities. You are entrusted with concocting quarterly figures for a thing that seems to have level, irregularity, and pattern. While the organization has some data, nobody understands what the boundaries (, , or ) are.

You have a few data. For instance, you realize that verifiably, the interest in each quarter follows this circulation: - Data 1 (Jan through Mar) = 60% of normal quarterly interest - Data 2 (April through June) = 80% of normal quarterly interest - Data 3 (July through Sep) = 140% of normal quarterly interest Data 4 (Oct through Dec) = 120% of normal quarterly interest.

You just ran the gauge toward the finish of September (end of 2015Q3) and you have the accompanying estimations:

For level: a^2015Q3 = 1051 units

For trend: b^2015Q3= 40.5 units per quarter

*Please display step-by-step*

PART 1

What is your forecast for demand for 2015Q4? In other words, what is x^2015Q3,2015Q4? Your answer must be round to two decimal spots.

PART 2

Assume the genuine demand in 2015Q4 is 1050 units. What is the smallest possible value for your estimate for level, a^2015Q4? Your answer must be adjusted to two decimal spots.

PART 3

The model was run at the end of 2015Q4. It provided you with the most recent estimates of each pattern. The estimate for level, a^2015Q4 was 1067.8. What is the estimation of ? Your answer must be round to two decimal spots.

PART 4

The model was run at the end of 2015Q4. The estimate for trend, 20154 was found to be 39.6. What is the estimation of ? Your answer must be adjusted to two decimal spots.

PART 5

The model was run toward the finish of2015Q4. The estimate for seasonality, 20154 was found to be 1.189, before any normalization was done. What is the estimation of ? Your answer must be adjusted to two decimal spots.