What is Statistical Data Analysis

Statistical Data Analysis

Statistical data analysis usually contains some arrangement of statistical tools, which a common man cannot perform without having any statistical know how. There are various software packages to perform statistical data analysis. This software includes Statistical Package for the Social Sciences SPSS, Statistical Analysis System (SAS) etc.

Statistical data analysis consists of variables. Sometimes the data is univariate or multivariate. It depends upon the number of variables; the scholar accomplishes different statistical techniques.

Data in statistical data analysis is numerous in numbers, then several multivariate can be performed. These are factor statistical data analysis, discriminant statistical data analysis, etc. In another case, if the data is singular in number, then the univariate statistical data analysis is performed. This includes ANOVA one way, f test, t test for significance, z test etc.

Types of Statistical Data Analysis

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

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.

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

Function of Statistical Data Analysis 

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.

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

Hypothesis using Statistical Data 

There is a chief task in statistical data analysis, which contains statistical inference. The statistical inference is mainly covered with two parts: estimation and tests of hypothesis.

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