4. Using the actual Year-3 numbers check your forecast accuracy, by calculating CFE, MSE, MAD, MAPE, and the tracking signal on microsoft Excel ### Dress Sales Data AnalysisPricilla Phranklin opened her clothing store, Pricilla Phashions, in Downtown Dover a little over three years ago. The sales of pants, skirts, blouses, and shirts are fairly consistent, while items like shorts, sweaters, and outerwear show a high degree of seasonality. However, the sales of dresses are more challenging to predict. Pricilla is hiring you to determine the best forecasting method for dress sales.Below is a table containing three years of dress sales data:| Month | Year 1 Demand | Year 2 Demand | Year 3 Demand ||-------|---------------|---------------|---------------|| Jan | 186 | 217 | 212 || Feb | 222 | 220 | 245 || Mar | 220 | 239 | 252 || Apr | 356 | 362 | 376 || May | 720 | 727 | 757 || Jun | 367 | 376 | 404 || Jul | 340 | 341 | 354 || Aug | 293 | 290 | 324 || Sep | 305 | 296 | 338 || Oct | 600 | 600 | 618 || Nov | 325 | 318 | 356 || Dec | 679 | 708 | 713 || **Total** | **4613** | **4694** | **4949** |This data will help in analyzing the patterns and trends in dress sales over a three-year period, which is essential for developing a robust forecasting model. The data shows variability across months, indicating potential seasonality, and an overall increasing trend.

Given information: Month Year 1 Demand Year 2 Demand Year 3 Demand January 186 217 212…

Pricilla Phranklin opened her clothing store, Pricilla Phashions, in Downtown Dover a little over three years ago. Pants, skirts, blouses, and shirts have fairly consistent sales, while things like shorts, sweater and outerwear are highly seasonal. On the other hand, dresses are a little harder to predict. Pricilla is hiring you to arrive at the best forecasting method for dresses. The following table contains three years of dress sales data Year 1 Month Demand Jan Feb Mar Apr Ap May Jun ww Jul . Aug Sep Oct Nov Dec Total 186 222 *********** Year 2 Demand 217 220 239 2.99 362 www 727 *** 376 www 341 290 296 600 318 708 4694 Year 3 Deman d 212 245 252 376 919 757 10 404 354 324 338 618 356 713 4949

Pricilla Phranklin opened her clothing store, Pricilla Phashions, in Downtown Dover a little over three years ago. Pants, skirts, blouses, and shirts have fairly consistent sales, while things like shorts, sweater and outerwear are highly seasonal. On the other hand, dresses are a little harder to predict. Pricilla is hiring you to arrive at the best forecasting method for dresses. The following table contains three years of dress sales data Year 1 Month Demand Jan Feb Mar Apr Ap May Jun ww Jul . Aug Sep Oct Nov Dec Total 186 222 ********* Year 2 Demand 217 220 239 2.99 362 www 727 * 376 www 341 290 296 600 318 708 4694 Year 3 Deman d 212 245 252 376 919 757 10 404 354 324 338 618 356 713 4949

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Question

4. Using the actual Year-3 numbers check your forecast accuracy, by calculating CFE, MSE, MAD, MAPE, and the tracking signal on microsoft Excel

### Dress Sales Data Analysis

Pricilla Phranklin opened her clothing store, Pricilla Phashions, in Downtown Dover a little over three years ago. The sales of pants, skirts, blouses, and shirts are fairly consistent, while items like shorts, sweaters, and outerwear show a high degree of seasonality. However, the sales of dresses are more challenging to predict. Pricilla is hiring you to determine the best forecasting method for dress sales.

Below is a table containing three years of dress sales data:

| Month | Year 1 Demand | Year 2 Demand | Year 3 Demand |
|-------|---------------|---------------|---------------|
| Jan | 186 | 217 | 212 |
| Feb | 222 | 220 | 245 |
| Mar | 220 | 239 | 252 |
| Apr | 356 | 362 | 376 |
| May | 720 | 727 | 757 |
| Jun | 367 | 376 | 404 |
| Jul | 340 | 341 | 354 |
| Aug | 293 | 290 | 324 |
| Sep | 305 | 296 | 338 |
| Oct | 600 | 600 | 618 |
| Nov | 325 | 318 | 356 |
| Dec | 679 | 708 | 713 |
| **Total** | **4613** | **4694** | **4949** |

This data will help in analyzing the patterns and trends in dress sales over a three-year period, which is essential for developing a robust forecasting model. The data shows variability across months, indicating potential seasonality, and an overall increasing trend.

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