This week is dedicated to Time-Series Forecasting techniques. Start in the Lessons section of the classroom by completing the reading and viewing assignments. Don’t even think about trying to complete this homework assignment without understanding the concepts involved in Forecasting Time-Series data. Once you have the concepts down in chapter 5, and have completed the Discussion forum, you are ready to start this assignment. Download the Excel Template attached to this assignment onto your computer, open it up, and read through the “Red Snapper Scenario” at the top of the page. All of this week’s assignments focuses on historical Red Snapper Catches for 2015 through 2018 (by Quarter) off the coast of Louisiana. The last four rows of the table are empty as 2019 is what you are going to forecast using the historical data for 2015 through 2018. As you scroll down through the Spreadsheet, you will notice in the far left column, there are five tasks for you to complete this week. Every one of these tasks is mirrored in the three YouTube videos below. Although this project is about Red Snapper Catches (your faithful designer’s favorite fish to catch and eat out of the southern bays of Louisiana) and the videos forecast Car sales, the process for forecasting the future year (in our case 2019) is identical.
You will want to watch these videos as you complete each of the five tasks. Where you want to transition from video 1 to video 2 and from video 2 to video 3 is very easy to see. One easy way to get started is to have a video open on one side of your screen and the excel template on the other.
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>Red Snapper Forecast
: You have been asked to analyze the trends in Red Snapper taken out of the coastal waters of Louisiana. The data (in Tons) for the last four years is recorded in the table below. There are Tasks you will need to complete in this Time-Series Data Analysis and forecasting.
ly data Red Snapper Take in tons 5 – 201 and Forecast for 201 t Quarter 0) Yt
& It Yt/CMA
1 1 . 3
2 2 .90
3 3 4 4 5 1 1.21 6 2 1.58 7 3 0.84 8 4 9 1 1.21 10 2 1.58 3 0.83 4 0.40 1 1.21 2 1.58 15 3 0.84 16 4 4.56 0.40 17 1 1.21 18 2 2.30 1.58 19 3 0.84 20 4 0.40 This step has been completed for you, however it will help you to understand how this was done Quarter 1 2 3 4
2
Assignment Week
5
4
Historical
Quarter
20
1
8
9
Year
Tons (x
10
MA (Moving Average)
CMA
St
Seasonal Trend St
DeSeasonalize Yt /St
Trend Component Tt (Uses the Regression Formula Created in Step 4)
Forecast St x Tt
20
15
4.50
1.21
3
7
6
1.58
4.36
3.20
4.05
4.
18
0.77
0.84
3.81
1.60
4.30
4.41
0.36
0.398
4.02
20
16
5.50
4.53
4.64
1.
19
4.56
7.80
4.75
4.78
1.63
4.93
4.10
4.80
4.91
0.83
4.88
1.80
5.03
5.20
0.35
0.40
4.52
20
17
6.40
5.38
5.46
1.17
5.30
9.20
5.55
5.60
1.64
5.81
11
4.80 5.65
5.76
0.84 5.71
12
2.20
5.88
5.80
0.38
5.53
13
2018
7.30
5.73
5.78
1.26
6.05
14
8.60
5.83
5.84
1.47
5.43
5.20 5.85
5.61
0.93
6.19
2.30
5.37
0.50
5.78
2019
3.75
Task 1
Create a Time series visualization of the historical take of Red Snapper by creating a line chart
with markers, by year and quarter, and with an appropriate title. Do not use Column C for this plot, only D, e, and F
Start by highlighting the column headings and then all data down through Quarter 4. Follow the directions for
creating this chart given in the “Excel Time Series Part 1 of 3” in the classroom under Week 5 Lesson.
Information
Next you need a Moving Average of 4 months in Column G. This procedure is explained in the “Excel Time Series Part 1 of 3”
at approximately the 11 minute point in the video. Column H has been completed for you showing a Centered Moving average (Time
Stamp 12:30.
This step has been completed for you, however it will help you to understand how this was done
Refer to the Lesson Video titled “Excel – Time Series Forecasting – Parts 2 of 3
Information
In this step, we need to extract the seasonality (St) in the data. It has already been completed for you in the table below, however please view and follow the video instructions to see how this was done. The seasonality factors have all been inserted for you by quarter in the table above. Finally, this allows us to finish the “DeSeasonalizes” in column K
St
1.21
1.58
0.84
0.40
Refer to the Lesson Video titled “Excel – Time Series Forecasting – Parts 3 of 3 to complete Task 4
Task 2
In this Task, you will be creating a Trend component in Column L. To calculate the “Trend Component” ( Tt ) you will need to Create a regression analysis using the “Deseasonalized Data” as the Y-variable (in Column K) and “t” (time period in Column C) as our X-variable. Make sure you pick up only the rows with data, not the 2019 Forecast rows (17 – 20). Use Data -> Data Analysis -> Regression. Follow the instructions on the Video (Part 3 of 3) to complete this part of the analysis. When asked where to insert the regression Analysis use B71. The constants you receive from the regression analysis will be used in Task 2
Task 3
Now that our Regression Analysis has given us our two constants, we can use these to complete the Trend Component Tt (in Column L) You need to create an Excel formula using Trend Component = intercept Constant + x-variable constant*t). You can now complete Column L for Rows 6 through 25
Tasks 4 & 5
You are now ready to complete the “Forecast Column” (Column M) for each of the 16 periods of existing data and the Forecast period for 2019 (Rows 22 – 25). The Forecast column is created by multiplying the Trend component (column L) by the Seasonal Trend (column J). Finally, in the space below, Create a final Line Chart Plot of the forecasted data (Column M) through all 5 years (2015 – 2019). Add a trend line to this Line Chart Plot.
image1
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