Statistics: Descriptive and Inferential
Statistics plays a main role in the field of research. It helps us in the collection, analysis and presentation of data. In this blog post we will try to learn about the two main branches of statistics that is descriptive and inferential statistics.
Statistics is concerned with developing and studying different methods for collecting, analyzing and presenting the empirical data.
The field of statistics is composed of two broad categories- Descriptive and inferential statistics. Both of them give us different insights about the data. One alone doesn’t not help us much to understand the complete picture of our data but using both of them together gives us a powerful tool for description and prediction.
Before starting with descriptive and inferential statistics let us get the basic idea of population and sample.
Population:
Population is the group that is targeted to collect the data from. Our data is the information collected from the population. Population is always defined first, before starting the data collection process for any statistical study. Population is not necessarily be people rather it could be batch of batteries, measurements of rainfall in an area or a group of people.
Sample:
It is the part of population which is selected randomly for the study. The sample should be selected such that it represents all the characteristics of the population. The process of selecting the subset from the population is called sampling and the subset selected is called the sample.
Descriptive Statistics
It describes the important characteristics/ properties of the data using the measures the central tendency like mean/ median/mode and the measures of dispersion like range, standard deviation, variance etc.
Data can be summarized and represented in an accurate way using charts, tables and graphs.
For example: We have marks of 1000 students and we may be interested in the overall performance of those students and the distribution as well as the spread of marks. Descriptive statistics provides us the tools to define our data in a most understandable and appropriate way.
Inferential Statistics
It is about using data from sample and then making inferences about the larger population from which the sample is drawn. The goal of the inferential statistics is to draw conclusions from a sample and generalize them to the population. It determines the probability of the characteristics of the sample using probability theory. The most common methodologies used are hypothesis tests, Analysis of variance etc.
For example: Suppose we are interested in the exam marks of all the students in India. But it is not feasible to measure the exam marks of all the students in India. So now we will measure the marks of a smaller sample of students, for example 1000 students. This sample will now represent the large population of Indian students. We would consider this sample for our statistical study for studying the population from which it’s deduced.
Some differences to remember!
Thank you for reading!
