What is the importance of descriptive statistics?

Hint: We start the problem by recalling the basic definition of statistics and knowing the types of statistics. And then we learn about the definition of descriptive statistics and their definition, types and importance briefly.

Complete step by step solution:
Statistics is defined as the study of data collection, interpretation, presentation, and organizing in a specific way.
There are two types of statistics
1. Descriptive statistics
2. Inferential statistics
In descriptive statistics, the data is described in a summarized way. The summarization is done from the sample of the population using different parameters like mean or standard deviation. Descriptive statistics are a way of using charts, graphs, and summary measures to organize, represent, and explain a set of data.
The importance of descriptive statistics is
Data is typically arranged and displayed in tables or graphs summarizing details such as histograms, pie charts, bars or scatter plots.
Descriptive statistics are descriptive and usually don't require normalization beyond the data collected.
Descriptive statistics are very important because, if we represent any raw data it would be more confusable for understanding. So, this descriptive statistic makes us present the data in a more informative way.
Example: A college involves the average math test score for incoming students. It says nothing about why the data is. Descriptive statistics helps us to simplify huge amounts of data in an understandable way. It decreases lots of data into a summary.
Types of descriptive statistics
1. Frequency Distribution
2. Measure of Central Tendency
3. Measures of Variability

Note: We should have basic knowledge on the concept of statistics. As this topic helps us to solve many problems related to data collection, or if any survey conducts, we can easily simplify the data into a meaningful and understandable way. The descriptive statistics also enables us to summarize the data in an informative way.