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# A Definitive Guide to Descriptive Statistics

Published by at August 20th, 2021 , Revised On August 25, 2023

Descriptive statistics is the summarising and organising of the characteristics of a dataset. Data set is a collection, or a set of responses, hypotheses, or observations from a limited number of samples or an entire population (Mishra et al.2019).

While conducting quantitative research, the first step is the collection of data. Once the data has been collected, the research can proceed to analyse the data.

Data analysis takes place to narrate the characteristics of responses. For instance, an average of one entry or a variable (e.g. age or gender) or the correspondence between two variables ( e.g. age and creativity).

The next step in the process is inferential statistics. These are the tools used to decide whether the data uphold or invalidate your hypothesis and if this data can be generalised to a higher ranged population.

## Types of Descriptive Statistics

The three utmost types of descriptive statistics are as follows:

• The distribution which scrutinizes the frequency of each value.
• The central tendency which covers the value average.
• Variability or dispersion which is linked to the level up to which the values are spread out.

These can be used to assess only one variable at a particular time in the univariate analysis. Two or more variables can also be compared in bivariate and multivariate analysis (Kaliyadan et al., 2019).

The main purpose of descriptive statistics is to summarize and present data in a meaningful way. It helps in understanding the central tendency, dispersion, and shape of data distribution, making complex data sets more interpretable and providing insights for decision-making and analysis.