Difference between revisions of "ANLY482 AY2016-17 T2 Group10 Analysis & Findings"
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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> | + | ==<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>Data Preparation</strong></font></div>== |
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| + | 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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Revision as of 18:29, 21 February 2017
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.
