Difference between revisions of "ANLY482 AY2016-17 T2 Group19 Methodology"
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==<div style="background: #4d4d4d; padding: 20px; line-height: 0.1em; text-indent: 10px; font-size:20px; font-family: Trajan Pro; border-radius: 7px; border-bottom:3px solid #ba3749"><font color= #ffffff>Data Set Acknowledgement</font></div>== | ==<div style="background: #4d4d4d; padding: 20px; line-height: 0.1em; text-indent: 10px; font-size:20px; font-family: Trajan Pro; border-radius: 7px; border-bottom:3px solid #ba3749"><font color= #ffffff>Data Set Acknowledgement</font></div>== | ||
<div style="margin:0px; padding: 10px; background: #f2f4f4; font-family: Arial, sans-serif; border-radius: 7px; text-align:left"> | <div style="margin:0px; padding: 10px; background: #f2f4f4; font-family: Arial, sans-serif; border-radius: 7px; text-align:left"> | ||
| − | + | The raw data was collected from Company Z on the 12th of January 2016 and is described as follows: | |
| + | * Sales data from Pharmaceutical Wholesale Distributions | ||
| + | * Itemised transactions occurring in the years 2014 to 2016 | ||
| + | |||
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Revision as of 23:01, 25 February 2017
Data Set Acknowledgement
The raw data was collected from Company Z on the 12th of January 2016 and is described as follows:
- Sales data from Pharmaceutical Wholesale Distributions
- Itemised transactions occurring in the years 2014 to 2016
-Insert Name of Model
Explanation of the use of this model, why use this, any special treatment done in order to use this model?
Since logistic regression is sensitive to data with skewed distributions, it becomes important to standardize our continuous data to fit a normal distribution as closely as possible. This resulted in balance, duration, campaign, previous and pdays being transformed to provide a better fit for the model.
Steps and approach elaboration
