The coefficient is an index to measure the correlation between two sets of data.
If the value of coefficients are ≤ 0.35, it is generally
considered to express low or weak correlations. From 0.36 to 0.67, they are modest or moderate
correlations. From 0.68 to 1.0, they are strong or high correlations. With coefficients ≥ 0.90,
it will be very high correlations. However, it depends on the property of the data and for some of
values like 0.3 to 0.6 are meaningless to conclude something. The correlation coefficient
can be negative, which indicates that those two data inversely correlated. Similarly, when it becomes
close to -1.0, their opposite correlation is strong.

Detailed instruction of correlation coefficients

Sometimes, people feel that we should have used the other variables to express the answers from
a questionnaire. We can also think how we change the expressions for each presentation. If it is
a small amount of data, it will not be hard to replace manually. However, when you have
more than hundreds of data, it is not easy. Fortunately, there is a systematic tool to replace
the variables in Excel.

Detailed instruction of variable replacement

If you want to compare three variables or more than that, the pivot table is one of the useful
tools. You can see a value in terms of two parameters. The scheme can be extended to more
parameters to see a specific value.

Detailed instruction of pivot table

This test identifies the difference of average between two groups of data, which is also called
Student's t-test. It is based on testing null hypothesis that the averages of the two group are
equivalent. When it shows that the P value is less than 5%, we can reject the null hypothesis,
which these groups are significantly
different.

Detailed instruction of *t*-test

There are symbols and abbreviations for statistics expressions. This is a compilation of
these especially for novice.

Detailed instruction of statistical symbols

The probability distributions are used under different conditions. Here is a table to briefly explain
each distribution.

Detailed instruction of statistical distributions

This is a table for the conversion of the intrinsic functions and other useful commands in C/C++, Mathematica and
other languages.

Detailed instruction of conversions between program languages

This shows the format specifiers, escape sequences, etc. of Fortran and C/C++. The input and output of data
depends on programming languages. This makes easier to refer to many of the codes and options.

Detailed instruction of teh format, code, declaration of variables for programming languages

Learning pointers is not easy for most of the beginners. This explains the basic ideas of pointers and its applications.
You can understand the usefulness of pointers after reading this.

Detailed instruction of pointers

Sample code 1 (Function pointer 1),
Sample code 2 (Function pointer 2),
Sample code 3 (Newton's method)

This will show you examples of how we call some of mathematical symbols and expressions.

Detailed instruction of reading math expressions

Especially for mathematical expressions, people prefer to use LaTeX to design a document.
This is a basic instruction of how to get started with LaTeX.

The PDF file of how to manipulate LaTeX

The source file for MikTeX,
The picture file (jpg) for MikTex

The source file for Linux LaTeX,
The picture file (eps) for Linux LaTeX

There are well-known methods to generate various ideas, such as brainstorming, etc.
This file summerizes them so you can overlook each method.

Detailed instruction of how to generate ideas

The editor is text-based and widely used for coding. This is a reference especially for beginners.

Detailed instruction of *vi* editor

Java is a programming language that is based on an object-oriented paradigm. This explains the basic commands of Java and Java applets.

Detailed instruction of JAVA programming

Detailed instruction of Python