Social Complexity in 3D Lecture: http://youtu.be/eYe0QrFpQ6c

# Statistics

There are 3 posts filed in **Statistics**.

# Statistical analysis process

In a statistical analysis, there is a typical sequence of steps.

**Interview the data**– where did it come from? Is it high quality? Does it omit any details? Are omitted details important?- Check for
**significant correlation**– Are variables related to one another? What happens if you randomly re-distribute one or more variables? Is there a trend? Does it change with re-distribution? - Check for
**causality**– Does one variable affect the value of another**?** **Generalize**causality – Can the causality apply to broader contexts? Is causality limited to a certain area, scope, demographic, timeframe, etc?

Each step tends to refine data, questions, etc.. Some analysis attempts may not make it through the series of steps.

# Landscapes of Change – peer C02 Usage Analysis

Participants in Landscapes of Change provided CO2 usage data. Eight of the 34 participants (23%) provided data specific enough for comparison, in effect describing the tons of C02 estimated to sustain their current lifestyles.

The original samples, in tons of c02 per year, are

- 12.0
- 30.0
- 14.0
- 16.0
- 26.0
- 8.4
- 13.6
- 24.0

With so few observations, it is difficult to determine any statistically significant patterns.

Following are some basic general statistics, as I learn how to use R Studio.

- The sample
**average**is**18 tons per year**. - The group
**standard deviation**is**7.7**, meaning 68% of the participants use between 10.3 and 25.7 tons of c02 per year. - The histogram does not seem to follow a normal distribution.