Statistics And Graphs

Statistical Analysis and Producing Graphs

This page demonstrates through some simple examples how to use statistical tools to process your observations and create graphs for papers or presentations.

Initially, this tutorial will use SAS and gnuplot to create graphs. We should expand it to demonstrate how to use Matlab and SPSS which are also popular and powerful tools for doing statistics.

Examples

Example 1. You are interested in two visualization methods and want to compare the speed a task is completed with both. First, setup your experiment and collect your samples which might be of this form:

technique    time
1            12
2            7
1            13
2            9
1            20
2            10
1            16
2            12
1            13
2            15
1            14
2            6

Here on, we assume this data is stored in a text file named "data.txt".

The SAS script below can process the data and produce new files with statistical information and data suited to plotting with gnuplut. You could cut-and-paste the text into a file named "analyze_time_data.sas" to try it out.

*options pageno=1 formdlim='-';
options nonumber nocenter  nodate pagesize=8000;

data result;
infile 'data.txt';
input technique time;
cards;
*proc print;
run;

/* sort */
title 'result: just sort it';
proc sort data = result;
by technique;
*proc print;
run;

/* summary statistics */
title 'result: GLM test on time/tech';
proc glm data = result;
class technique;
model time = technique;
means technique / tukey;
run;

title 'result: mean summary statistics technique (time)';
proc means mean std data=result;
by technique;
var time;
output out=result_means MEAN=Mean STDDEV=StdDev;
proc export data=result_means outfile='graph_data.txt' replace;
proc print;
run;

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Example 2. You surveyed a population and want to run statistical analysis on the data collected and produce graphs showing the result.

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