Conduct a Paired T-Test Video

The video below demonstrates how to conduct a paired t-test.

Paired t Test from Statistics Solutions on Vimeo.



Statistics Solutions

Statistical Data Analysis

Statistics is basically a science that involves data collection, data interpretation and finally, data validation. Statistical data analysis is a procedure of performing various statistical operations. Statistical data analysis is a kind of quantitative research, which seeks to quantify the data, and typically, applies some form of statistical analysis. Quantitative data in statistical data analysis basically involves descriptive data, such as survey data and observational data.

Statistical data analysis generally involves some form of statistical tools, which a layman cannot perform without having any statistical knowledge. There are various software packages to perform statistical data analysis. This software includes Statistical Analysis System (SAS), Statistical Package for the Social Sciences (SPSS), Stat soft, etc.

Data in statistical data analysis consists of variable(s). Sometimes the data in statistical data analysis is univariate or multivariate. Depending upon the number of variables in statistical data analysis, the researcher performs different statistical techniques.

If the data in statistical data analysis is multiple in numbers, then several multivariate statistical data analysis can be performed. The multivariate statistical data analyses are factor statistical data analysis, discriminant statistical data analysis, etc. Similarly, if the data in statistical data analysis is singular in number, then the univariate statistical data analysis is performed. This includes t test for significance, z test, f test, ANOVA one way, etc.

The data in statistical data analysis is basically of 2 types, namely, continuous data and discreet data. The continuous data in statistical data analysis is the one that cannot be counted. For example, intensity of a light can be measured but cannot be counted. The discreet data in statistical data analysis is the one that can be counted. For example, the number of bulbs can be counted.

The continuous data in statistical data analysis is distributed under continuous distribution function, which can also be called the probability density function, or simply pdf.

The discreet data in statistical data analysis is distributed under discreet distribution function, which can also be called the probability mass function or simple pmf.

We use the word ‘density’ in continuous data of statistical data analysis because density cannot be counted, but can be measured. We use the word ‘mass’ in discreet data of statistical data analysis because mass cannot be counted.

There are various pdf’s and pmf’s in statistical data analysis. For example, Poisson distribution is the commonly known pmf, and normal distribution is the commonly known pdf in statistical data analysis.

These distributions in statistical data analysis help us to understand which data falls under which distribution. If the data in statistical data analysis is about the intensity of a bulb, then the data would be falling in Poisson distribution.

There is a major task in statistical data analysis, which comprises of statistical inference. The statistical inference in statistical data analysis is mainly comprised of two parts: estimation and tests of hypothesis.

Estimation in statistical data analysis mainly involves parametric data—the data that consists of parameters. On the other hand, tests of hypothesis in statistical data analysis mainly involve non parametric data— the data that consists of no parameters.

For more information on statistical consulting, click here.