Difference between revisions of "ISSS608 2016-17 T1 Assign2 XU Qiuhui"

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==Group Categorical Data==
 
==Group Categorical Data==
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Transform all survey question answers with 1-5 scores to “High, Mid, Low” degree.
  
 
=Visualization=
 
=Visualization=

Revision as of 11:52, 26 September 2016

Data Sources

Dataset from UCI, Survey of faculty members from two Spanish universities on teaching uses of Wikipedia

Source: E. Aibar, J. Lladós, A. Meseguer, J. Minguillón (jminguillona[at]uoc[dot]edu), M. Lerga. Universitat Oberta de Catalunya, Barcelona, Spain.

Theme of Interest and Motivation

This Analysis aims to find out users' overall impressions on Wikipedia and their use, as well as future expectation of Wikipedia according to high dimensional survey question answers. Then propose recommendations for Wikipedia's future development.

Data Preparation

Transfer Data Type

Variables Original Data Type Transferred Data Type Reason
Gender Numeric Categorical According to dataset dictionary, gender is meaningless while using numeric value to do analysis.
PhD Numeric Categorical According to dataset dictionary, PhD is meaningless while using numeric value to do analysis.
University Numeric Categorical According to dataset dictionary, University is meaningless while using numeric value to do analysis.
YearsExp Categorical Numeric Years of experience should be continuous data, so that we can firstly bin them into several groups, then use groups to classify them.

Bin Numeric Data

Variables Original Transferred Variables Formula
Age
Age
Age(bin) If(:AGE <= 30,"20~30",If(:AGE <= 40,"30~40",If(:AGE <= 50,"40~50",If(:AGE <= 60,"50~60","60~70"))))
YearsExp
YearsExp
YearsExp(bin) If( :YEARSEXP <= 10,"0~10",If( :YEARSEXP <= 20,"10~20",If( :YEARSEXP <= 30,"20~30","more than 30")))

Group Categorical Data

Transform all survey question answers with 1-5 scores to “High, Mid, Low” degree.

Visualization

Analysis

Tools Utilized