SIMPLE TIME SERIES ANALYSIS (EXPONENTIAL SMOOTHING) .
SIMPLE TIME SERIES ANALYSIS (EXPONENTIAL SMOOTHING). Another way to analyze fiscal data over time is via Time Series Analysis. Time series analysis enables public administrators
SIMPLE TIME SERIES ANALYSIS (EXPONENTIAL SMOOTHING)
Another way to analyze fiscal data over time is via Time Series Analysis.
Time series analysis enables public administrators and policy analysts to examine values of a variable over equally spaced intervals of time (e.g., income figures monthly or yearly).
Using times series analyses, administrators and analysts can discern patterns in the values that then enable them to forecast future values based on historical and existing patterns.
A time series plot allows an analyst to look for
(1) outliers and sudden shifts in data patterns,
(2) unusual observations or shifts,
(3) long-term increase or decrease in the data values.
A trend plot also will show whether the data pattern is linear, or nonlinear, as the time series plot. Then, the question to be asked is, why?
For this Module Assignment, students will compute and interpret a Simple Time Series Analysis called Exponential Smoothing, and also write a four-page report stating their findings, including chart(s). See the end of this assignment, How to Interpret the key results for Time Series Plot.
To do this:
First, to use the Exponential Smoothing feature in Excel, the Data Analysis ToolPak must been activated.
To see if Data Analysis ToolPak has been activated, look at the top middle of the excel screen and select Data, then look at the top right or the excel screen and look for Data Analysis. If you see it, you are ready to go. Go to the bottom of page 2, Procedure for calculating a Simple Time Series Analysis (Exponential Smoothing), and begin. If not, install the Data Analysis ToolPak by following the instructions below.
If you have any difficulties, contact me immediately by email or phone. I will walk you through the process.
To activate Data Analysis Toolpak
Data Analysis is available under the DATA tab in excel.
If you are not able to view this in your Excel spreadsheet, follow the below steps to enable “Data Analysis” in your excel workbook.
Click on FILE and Options.
Click on Add-Ins.
Under Add-Ins select “Excel Add-Ins” from manage options and click on Ok.
Now from the below window select “Analysis Toolpak” and click on OK to enable “Data Analysis”.
Now you should see “Data Analysis” under the “DATA” tab.
Once the Analysis ToolPak is activated follow the next steps.
Procedure for calculating a Simple Time Series Analysis (Exponential Smoothing):
Select Data Set (e.g., Income Data)
Open and save the income data in the spreadsheet (Excel)
Select Data at the top middle of the excel screen, then
Select Exponential Smoothing (click OK) from the list of Analysis Tools. (may have to scroll up or down)
Place cursor in Input Range and highlight data, including the column heading, that you want to analyze, in this, Individual Income
Place cursor in Output Range and highlight any area in the chart that is blank, say B16:D21.
Select Chart Output and Standard Errors
You will see a chart something like the one below:
Do not panic!
Place cursor on the chart and click You will see a round white dot, just below the term Data Point and drag down until the chart look like this:
Now, select Design at the top middle of the excel screen, then
select Add Chart Element
Select Data Labels > Below
How to Interpret the key results for Time Series Plot
Step 1: Look for outliers and sudden shifts
Use knowledge to determine whether unusual observations or shifts indicate errors or a real change in the process.
Outliers Look for unusual observations, also called outliers. Outliers can have a disproportionate effect on time series models and produce misleading results. Try to identify the cause of any outliers and correct any data-entry errors or measurement errors. Additionally, consider removing data values that are associated with abnormal, one-time events, which are also called special causes.
The following time series plot shows an outlier that was caused by a data-entry error. A technician accidentally entered the value 4 in the worksheet instead of 40.
Look for sudden shifts in the series or sudden changes to trends. Try to identify the cause of such changes.
For example, the following time series plot shows a drastic shift in the cost of a process after 15 months. You should investigate the reason for the shift.
Step 2: Look for trends
A trend is a long-term increase or decrease in the data values. A trend can be linear, or it can exhibit some curvature. If your data exhibit a trend, you can use a time series analysis to model the data and generate forecasts.
For more information on which analysis to use, go to Which time series analysis should I use?.
The following time series plot shows a clear upward trend.
There may also be a slight curve in the data, because the increase in the data values seems to accelerate over time.
Once the plot is completed, write a four-page report, including chart(s), interpreting the findings.
This is a Doctoral-level research assignment designed to test your ability to carefully research, effectively organize, and also concisely communicate a nuanced understanding of the concepts and issues raised in the assignment. While the minimum page limit is short (as is often the case in public policy/public administration briefings), students are expected to craft efficient, highly substantive papers. You are expected to comport with the highest writing, research, and ethical standards.
Plagiarism in any form is strictly prohibited and may result in failure of the assignment, failure of the course, and also removal from the program. It is your responsibility to ensure that you fully understand what constitutes the various forms of plagiarism and also that you avoid all forms of plagiarism.
Submit this assignment by 11:59 p.m. (ET) on Friday of Module/Week 8 – Classes end.
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