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

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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
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
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
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

# Simple statistical descriptive Models for the Web

- Formulating a research hypothesis and test it by means of simple descriptive statistics
- Reading diagrams

## Associated units

- Understand why we selected simple English Wikipedia as a toy example for modeling the web
- Understand that a task already as simple as counting words includes modeling choices
- Be familiar with the term “unique word token”
- Know some basic tools to count words and documents

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