Web Science/Part2: Emerging Web Properties/Simple statistical descriptive Models for the Web

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Simple statistical descriptive Models for the Web

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Learning goals

  1. Formulating a research hypothesis and test it by means of simple descriptive statistics
  2. Reading diagrams
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Associated units

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  1. Understand why we selected simple English Wikipedia as a toy example for modeling the web
  2. Understand that a task already as simple as counting words includes modeling choices
  3. Be familiar with the term “unique word token”
  4. Know some basic tools to count words and documents
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  • Be familiar with some basic statistical objects like Median, Mean, and Histograms
  • Should be able to relate a histogram to its cumulative distribution function
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  • Understand the ongoing, cyclic process of research
  • Know what falsifiable means and why every research hypothesis needs to be falsifiable
  • Be able to formulate your own research hypothesis
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  • Understand what a log-log plot is
  • Improve your skills in reading and interpreting diagrams
  • Know about the word rank / frequency plot
  • Should be able to transfer a histogram or curve into a cumulative distribution function
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  • Get a feeling for interdisciplinary research
  • Know the Automated Readability Index
  • Have a strong sense of support for our research hypothesis
  • Be able to critically discuss the limits of our models
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