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What is statistics, exactly?


The subject of statistics is mathematics. It is a true data analysis. It is the gathering, organization, analysis, interpretation, and presentation of data in order to obtain a meaningful result by collecting, confirming, analyzing, and interpreting a comprehensive set of data.


These fields provide the knowledge needed to work statistically with the data gathered. A technical and practical field is one of the many fields where statistical knowledge can be applied. Statistics are required for completion of all significant fields such as Economics, Business, Science, and Research.




The statistical calculation is the most significant pillar in managing enormous amounts of data quantitatively. Statistics are beneficial to the country and the enterprise in a variety of ways.


Here are some key facts that show why statistics is studied in college and university:


Why Learning statistics allows us to use the statistical instrument to execute our research tasks or projects more carefully and logically. So we can make a decision by logically evaluating the acquired facts with the help of a statistical tool.








Above are a few key points that demonstrate the importance of statistical research in this century. This can always be beneficial to the student in terms of developing new abilities.


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The following are the two primary branches of statistics:




Statistical descriptions


It is a method of summarizing and interpreting data in numerical or graphical form. Descriptive statistics necessitates the use of two sorts of statistical concepts. The first is a spread measure, sometimes known as a graphical summary. The graphical summary analyzes data through graphical representation.


The second is the numerical summary, which is a measure of central tendency. The mode is used to analyze the given data in the case of the numerical summary, mean, and median.


Statistical inference


It is a study that is carried out in order to infer or equate our findings to general conditions. This illustrates the distinction between inferential and descriptive statistics. Inferential statistics are applied to a wide range of statistical studies.


As a result, the sample, hypothesis testing, principal component analysis, and regression methods are utilized in inferential statistics. Using an example to help explain: If you need to compute the marks of 150 students in a class, you can use descriptive statistics, but if you need to calculate the marks of all Australian students, you’ll need to use inferential statistics, which requires drawing a valid sample from a specific population.


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