Difference between revisions of "ANLY482 AY2016-17 T2 Group19 Data"

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! style="border-style: none; border-width: 0 1px 1px 0; width: 12%"| [[ANLY482_AY2016-17_T2_Group19|<font color="#000000"><b>OVERVIEW</b></font>]]
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Revision as of 20:13, 10 January 2017



Protegelogo-01.svg

Protege overview.svg   OVERVIEW

Protege data.svg   DATA

Protege Methods.svg   METHODOLOGY

Protege Analysis.svg   ANALYSIS

Protegemaster-03.svg   FINDINGS

Protege poster.svg   POSTER

Data

Background

In the pharmaceutical industry, it has historically been a challenge to manage hundreds of hospitals and clinics with sizeable differences in the types of drugs, disposable items and the sheer volume in respective purchase orders

While not exclusive to this industry alone, managerial decision making processes have historically relied heavily on transactional raw data and managerial experience

The data set that was used contains sales data from a medium-sized pharmaceutical company with customer base ranging from over the counter pharmacies to clinics around Singapore.


Data Description

  1. insert table format of data set, only if not sensitive

Purpose of the model

Given the context of this data set...

Through these model...

Data Exploration

Categorical Data

-Insert title of variable-
-Insert Description of variable and comment on the preparatory work to be done-

  1. insert image if any


Continuous Data

-Insert title of variable-
-Insert Description of variable and comment on the preparatory work to be done-

  1. insert image if any


Multicollinearity

-Discuss any overlapping collinearity

  1. insert image if any



Data Cleaning and Preparation

-insert variable that has been cleaned-
-discuss the treatment and why the treatment-


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