Difference between revisions of "ANLY482 AY2016-17 T2 Group10 Analysis & Findings"
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<div style="margin:0px; padding: 10px; background: #f2f4f4; font-family: Century Gothic, Open Sans, Arial, sans-serif; border-radius: 7px; text-align:left; font-size: 15px"> | <div style="margin:0px; padding: 10px; background: #f2f4f4; font-family: Century Gothic, Open Sans, Arial, sans-serif; border-radius: 7px; text-align:left; font-size: 15px"> | ||
Exploratory Data Analysis is the approach to understand main characteristics of datasets through use of graphical techniques such as bar chart, histogram, and scatterplot. Our main responsibility for EDA lies in determining relationships among explanatory and response variables, and in doing so, generate insights on ways to tackle aforementioned business problems. | Exploratory Data Analysis is the approach to understand main characteristics of datasets through use of graphical techniques such as bar chart, histogram, and scatterplot. Our main responsibility for EDA lies in determining relationships among explanatory and response variables, and in doing so, generate insights on ways to tackle aforementioned business problems. | ||
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+ | ==<div style="background: #ffffff; padding: 17px;padding:0.3em; letter-spacing:0.1em; line-height: 0.1em; text-indent: 10px; font-size:17px; text-transform:uppercase; font-weight: light; font-family: 'Century Gothic'; border-left:8px solid #1b96fe"><font color= #000000><strong>MCCP</strong></font></div>== | ||
+ | <div style="margin:0px; padding: 10px; background: #f2f4f4; font-family: Century Gothic, Open Sans, Arial, sans-serif; border-radius: 7px; text-align:left; font-size: 15px"> | ||
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+ | ==<div style="background: #ffffff; padding: 17px;padding:0.3em; letter-spacing:0.1em; line-height: 0.1em; text-indent: 10px; font-size:17px; text-transform:uppercase; font-weight: light; font-family: 'Century Gothic'; border-left:8px solid #1b96fe"><font color= #000000><strong>Invoice Details</strong></font></div>== | ||
+ | <div style="margin:0px; padding: 10px; background: #f2f4f4; font-family: Century Gothic, Open Sans, Arial, sans-serif; border-radius: 7px; text-align:left; font-size: 15px"> | ||
+ | ===<span style="line-height: 0.1em;text-indent: 10px;background-color:#1b96fe;padding:5px;border-radius:5px;font-size:15px"><font color="white">Relationship between Sales, Price for different Channels</font></span>=== | ||
+ | We want to identify any purchasing patterns on sales and price by different channels (GP, Hospital, Pharmacy). We will follow the assumption that sales per transaction is an estimator of demand. | ||
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+ | ===<span style="line-height: 0.1em;text-indent: 10px;background-color:#1b96fe;padding:5px;border-radius:5px;font-size:15px"><font color="white">Relationship between No. of Transactions and Channels by Products</font></span>=== | ||
+ | We would like to determine purchasing pattern on frequencies of transactions based on different channels and products. | ||
</div> | </div> | ||
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Revision as of 18:33, 21 February 2017
Contents
Data Preparation
Exploratory Data Analysis is the approach to understand main characteristics of datasets through use of graphical techniques such as bar chart, histogram, and scatterplot. Our main responsibility for EDA lies in determining relationships among explanatory and response variables, and in doing so, generate insights on ways to tackle aforementioned business problems.
MCCP
Invoice Details
Relationship between Sales, Price for different Channels
We want to identify any purchasing patterns on sales and price by different channels (GP, Hospital, Pharmacy). We will follow the assumption that sales per transaction is an estimator of demand.
Relationship between No. of Transactions and Channels by Products
We would like to determine purchasing pattern on frequencies of transactions based on different channels and products.