# cbind

## Hierarchical Linear Model

Linear regression probably is the most familiar technique in data analysis, but its application is often hamstrung by model assumptions. For instance, if the data has a hierarchical structure, quite often the assumptions of linear regression are feasible only at local levels. We will investigate an extension of the linear model to bi-level hierarchies.

## Significance Test for Kendall's Tau-b

A variation of the standard definition of Kendall correlation coefficient is necessary in order to deal with data samples with tied ranks. It known as the Kendall’s tau-b coefficient and is more effective in determining whether two non-parametric data samples with ties are correlated.

## Kendall Rank Coefficient

The correlation coefficient is a measurement of correlation between two random variables. While its computation is straightforward, it is not readily applicable to non-parametric statistics.

## Matrix Construction

A discussion on various ways to construct a matrix in R.

## Chi-squared Test of Independence

A tutorial on performing the Chi-squared goodness of fit test for independent variables.

## Scatter Plot

A tutorial on computing the scatter plot of quantitative data in statistics.

## Frequency Distribution of Quantitative Data

A tutorial on computing the frequency distribution of quantitative data in statistics.