# Case 1

Submitted By jimmyisbett3r
Words 327
Pages 2
1) To analyze any time series data the best practice is to plot the scatter diagram at the beginning.
A scatter diagram tells us about the pattern of the time series data which should be accounted for when the forecasting model is being developed.
Here the obtained scatter plot is given below,

Scatter diagram
Number of patients

120
100
80
60
40
20
0
7/30/2014

8/4/2014

8/9/2014

8/14/2014 8/19/2014 8/24/2014 8/29/2014

9/3/2014

Date

Here we can see that the values are very close to each other and the random pattern is really limited. So a time series model is expected to well justify the situation.
2) In this case using a simple linear regression method the obtained regression model is,
Number of patients = 66.7806+0.9895*Time period.
The time period is variable created from the dates. Time period is representing the date starting from 8/1/2014, so time period = 1 represents 8/1/2014, time period = 2 represents 8/2/2014 and so on.
As my birthday is on 31st so the predicted number of patients at 1st October using the above regression equation is (note that for Sept has 30 days so 31st means 1st Oct and the time period value is for 1st Oct is 62)
Number of patients = 66.7806+0.9895*62 = 128.13
3) My birthday is an odd number so I am using the smoothing parameter 0.3. Using the exponential method the forecast for September 1 is 95.11.
4) From this case analysis I learned that in most of the situation a time series data can be modeled.
There are different models which should be tried to check which fits the data best. However choosing the correct model also depends on the pattern of the data. Here a linear pattern is prominent so a linear trend is more suitable....

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