DATA + DESIGN 資料＋設計
  • Introduction
  • Introduction
    • License
    • Preface
    • Foreword
    • How to Use This Book
  • Data Fundamentals
    • Basic Data Types
    • About Data Aggregation
  • Collecting Data
    • Intro to Survey Design
    • Types of Survey Questions
    • Additional Data Collection Methods
    • Finding External Data
  • Preparing Data
    • Getting Data Ready for Cleaning
    • Data Cleaning
    • Types of Data Checks
    • What Data Cleaning Can and Can’t Catch
    • Data Transformations
  • Visualizing Data
    • Deciding Which and How Much Data to Illustrate
    • Graphing the Results of Checkbox Responses
    • Anatomy of a Graphic
    • Importance of Color, Font, and Icons
    • Print Vs. Web, Static Vs. Interactive
  • What Not To Do
    • Perception Deception
    • Common Visualization Mistakes
  • Conclusion
    • Resources
    • Glossary
    • Contributors
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Resources

Chapter 3: Intro to Survey Design

Online survey sites

Kwik Surveys,

Free Online Surveys,

Google Forms,

Survey Gizmo,

Survey Monkey,

Survey Planet,

Chapter 4: Types of Survey Questions

Conducting Surveys

Dierckx, Didier. "The Case of 'Likert Scales v. Slider Scales,' Market Research (blog) Checkmarket.com,

Fink, Arlene. How to Conduct Surveys: A Step-by-Step Guide, 3rd ed., Thousand Oaks, California: SAGE Publications, Inc., 2006.

Fowler, Floyd J. Survey Research Methods, 5th ed., Thousand Oaks, California: SAGE Publications, Inc., 2014.

Gray, George and Neil Guppy. Successful Surveys: Research Methods and Practice, 3rd ed., Scarborough, Ontario: Thomson Nelson, 2003.

Chapter 7: Getting Data Ready for Cleaning

Splitting delimited text into columns in Excel

Splitting strings

JavaScript

Visual Basic

String Operations in Python

Missing Data

Osborne, Jason W., "Dealing with Missing or Incomplete Data: Debunking the Myth of Emptiness," Ch 6, Best Practices in Data Cleaning, Los Angeles, CA: SAGE Publications, Inc, 2013:

Chapter 8: Data Cleaning

Spreadsheet software

Regular Expressions

Guides and Testers

JavaScript

Python

Chapter 10: What Data Cleaning Can and Can't Catch

Data Transformations

"Scaled Questions," Instructional Assessment Resources, The University of Texas at Austin,

"Split text into different cells," Microsoft Office Support,

"JavaScript String split() Method," W3Schools,

"Split Function (Visual Basic)," Microsoft Developer Network,

"Common string operations," The Python Standard Library, Python Software Foundation,

"List of spreadsheet software," Wikipedia,

"Regular Expressions - User Guide," Zytrax,

RegExr v2.0,

"JavaScript RegExp Reference," W3Schools,

"Regular expression operations," The Python Standard Library, Python Software Foundation,

"Transformations to Achieve Linearity," Stat Trek,

http://www.kwiksurveys.com
http://www.freeonlinesurveys.com
http://www.google.com/google-d-s/createforms.html
http://www.surveygizmo.com
https://www.surveymonkey.com
https://www.surveyplanet.com
https://www.checkmarket.com/2012/08/likert_v_sliderscales/
http://www.utexas.edu/academic/ctl/assessment/iar/teaching/plan/method/survey/responseScale.pdf
http://office.microsoft.com/en-us/excel-help/split-text-into-different-cells-HA102809804.aspx
http://www.w3schools.com/jsref/jsref_split.asp
http://msdn.microsoft.com/en-us/library/6x627e5f(v=vs.90).aspx
https://docs.python.org/2/library/string.html
http://en.wikipedia.org/wiki/List_of_spreadsheet_software
http://www.zytrax.com/tech/web/regex.htm
http://www.regexr.com
http://www.w3schools.com/jsref/jsref_obj_regexp.asp
https://docs.python.org/2/library/re.html
http://stattrek.com/regression/linear-transformation.aspx#
  • Resources
  • Chapter 3: Intro to Survey Design
  • Online survey sites
  • Chapter 4: Types of Survey Questions
  • Conducting Surveys
  • Chapter 7: Getting Data Ready for Cleaning
  • Splitting delimited text into columns in Excel
  • Splitting strings
  • String Operations in Python
  • Missing Data
  • Chapter 8: Data Cleaning
  • Spreadsheet software
  • Regular Expressions
  • Chapter 10: What Data Cleaning Can and Can't Catch
  • Data Transformations
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  1. Conclusion

Resources