ISSS608 2016-17 T1 Assign2 XU Qiuhui
Contents
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(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(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.
Scores | Degree |
---|---|
1 | Low |
2 | Low |
3 | Mid |
4 | High |
5 | High |
Visualization
Analysis
Tools Utilized
- High-D - For initial data exploration and analysis
- JMP 12, MS Excel – For data preparation
- d3.js - For data visualization