Descriptive vs Inferential statistics

This blog explains about what is the difference between Descriptive statistics and Inferential statistics.

Descriptive statistics and inferential statistics are two different things. These terms have various analyses and different implications. People use them for different purposes, but they often need clarification because they both contain the words statistics! I will list some features and characteristics of descriptive and inferential statistics to clarify the difference.

Let us start with,

Descriptive Statistics.

Descriptive statistics aims to obtain individual numbers that characterize features of a sample dataset or any data set. For example, we can have characteristics of central tendency, dispersion characteristics, or the distribution's overall shape. If these are time series data, we might be interested in the frequency domain spectrum of the signal. So these are just some examples of descriptive statistics. Well, these are the most common descriptive statistics that people use. But they are not the only ones. Now, essential to note when we're talking about descriptive statistics, we do not care about the relationship between our sample data and the population from which those samples were drawn. We're not trying to generalize our samples to other samples or populations.

We're not trying to compare the characteristics of one data set with the attributes of a different dataset. That's not the point of descriptive statistics. The point of descriptive statistics is to have a small number of numbers.

Now, let's focus on,

Inferential statistics.

Inferential statistics uses features of a sample data set to make generalizations and claims about a population from which that sample was drawn.

So, the kinds of numbers associated with inferential statistics are the P and T values, F values, Chi-square values, confidence intervals, and hypothesis testing.

So, The entire purpose of Inferential statistics is to relate our data features to populations, generalize to other groups or compare different values between data sets or groups within a data set. Again, we want to compare our results across different samples or generalize our results from a sample to a population. With Descriptive statistics, we're not trying to make any comparison. We're not trying to make any generalizations. All we are trying to do is characterize a particular dataset. So that is the crucial set of differences between descriptive statistics and inferential statistics.

It's easy to confuse them when you are new to statistics because they both have the word

statistics, which is unfortunate. We should have come up with different names.

But, you know, I wasn't involved in that nomenclature for statistics, so.

So, I can't take any of the blame here anyway!!