File IO and Statistical Examples
GNU Octave, version 2.1.33 (i386-redhat-linux-gnu).
Copyright (C) 1996, 1997, 1998, 1999, 2000, 2001 John W. Eaton.
This is free software with ABSOLUTELY NO WARRANTY.
For details, type `warranty'.
*** This is a development version of Octave. Development releases
*** are provided for people who want to help test, debug, and improve
*** Octave.
***
*** If you want a stable, well-tested version of Octave, you should be
*** using one of the stable releases (when this development release
*** was made, the latest stable version was 2.0.16).
octave:1> ls
diary file_io.data junk session simple_octave.html
octave:2> dir
diary file_io.data junk session simple_octave.html
octave:3>
octave:3> # load the file data
octave:3> load file_io.data
octave:4> file_io
file_io =
4.50000 8.00000 3.00000 0.00000
6.80000 7.00000 3.00000 0.00000
10.50000 6.00000 6.00000 1.00000
15.50000 3.00000 6.00000 1.00000
16.00000 4.00000 6.00000 2.00000
18.90000 2.00000 6.00000 2.00000
23.50000 -1.00000 0.00000 2.00000
33.60000 -5.00000 0.00000 3.00000
34.80000 -5.00000 0.00000 3.00000
octave:5> # This is meaningless data, but has two ratio/interval variables
octave:5> # in columns 1 and 2, an ordinal variable in column 3 and the
octave:5> # class in column 4 is a nominal variable.
octave:5>
octave:5> x = file_io
x =
4.50000 8.00000 3.00000 0.00000
6.80000 7.00000 3.00000 0.00000
10.50000 6.00000 6.00000 1.00000
15.50000 3.00000 6.00000 1.00000
16.00000 4.00000 6.00000 2.00000
18.90000 2.00000 6.00000 2.00000
23.50000 -1.00000 0.00000 2.00000
33.60000 -5.00000 0.00000 3.00000
34.80000 -5.00000 0.00000 3.00000
octave:6>
octave:6> # Get the basic statistics
octave:6>
octave:6> mean (x)
ans =
18.2333 2.1111 3.3333 1.5556
octave:7> var (x)
ans =
116.2950 23.6111 7.7500 1.2778
octave:8> std (x)
ans =
10.7840 4.8591 2.7839 1.1304
octave:9>
octave:9> # make a new matrix for variables 1 and 4
octave:9> y = [x(:,1) x(:,4)]
y =
4.50000 0.00000
6.80000 0.00000
10.50000 1.00000
15.50000 1.00000
16.00000 2.00000
18.90000 2.00000
23.50000 2.00000
33.60000 3.00000
34.80000 3.00000
octave:11>
octave:11> # plot y
octave:11>
octave:11> gplot y with points
octave:12>
octave:12> # or you can use
octave:12> plot (y, "@")
octave:12>
octave:13> # Get the covariance matrix
octave:13>
octave:13> cov (x)
ans =
116.2950 -52.1292 -18.4625 11.5917
-52.1292 23.6111 8.9583 -5.0694
-18.4625 8.9583 7.7500 -1.3333
11.5917 -5.0694 -1.3333 1.2778
octave:14>
octave:14>
octave:14> # Get the correlation matrix
octave:14>
octave:14> cor (x)
ans =
1.00000 -0.99481 -0.61498 0.95091
-0.99481 1.00000 0.66224 -0.92294
-0.61498 0.66224 1.00000 -0.42370
0.95091 -0.92294 -0.42370 1.00000
octave:15>
octave:15> # This is the Pearson's Correlation Coefficient (Pearson's r)
octave:15> # so it makes sense only for the first two variables.
octave:15>
octave:15>
octave:15> # Calculate some other correlations
octave:15> spearman ([x(:,3) x(:,4)])
ans =
1.00000 -0.42230
-0.42230 1.00000
octave:16> spearman (x)
ans =
1.00000 -0.97909 -0.50780 0.97040
-0.97909 1.00000 0.50993 -0.93135
-0.50780 0.50993 1.00000 -0.42230
0.97040 -0.93135 -0.42230 1.00000
octave:17>
octave:17>
octave:17> kendall ([x(:,3) x(:,4)])
ans =
1.00000 -0.28645
-0.28645 1.00000
octave:18>
octave:18> kendall (x)
ans =
1.00000 -0.92967 -0.32686 0.91287
-0.92967 1.00000 0.33150 -0.86410
-0.32686 0.33150 1.00000 -0.28645
0.91287 -0.86410 -0.28645 1.00000
octave:19>
octave:19> # Save the session for a future time
octave:19>
octave:19> save file_io_sessions
octave:20> exit