What is statistics?

What is statistics?

Statistics is the science of data collection, data analysis, data interpretation, data presentation and data organization. Statistics is a branch of mathematics under applied mathematics. Statistics deals with uncertainty and variation variables. The two major areas of statistics are inferential statistics and descriptive statistics.

Sir Ronald Aylmer Fisher is considered as the father of modern statistics. However, Prasanta Chandra Mahalanobis is considered as the father of Indian statistics.

Types of statistics

Statistics is descriptive or inferential. Let us understand both these concepts:

Descriptive statistics: In the descriptive statistics, the data is presented in a summarized manner. The sample data population is summarized using statistical techniques like mean, median or mode. The summarization can be done in the form of charts, graphs, to explain the summarization of a particular data set. Since its just descriptive, there is no need for any normalization.

Inferential statistics: Inferential statistic is applied over the descriptive statics. The descriptive statistics provides description of the data set and inferential statistics interprets the summary of the descriptions. Inferential statistics intends to test the hypothesis, examines the relation between variables, and make predictions.

Why is statistics important?

Statistics is an important aspect of modern math as this incredible science helps to draw inferences and conclusions from a given data set. We can understand how things change over time with statistics. Statistics also helps to make predictions of future behaviours and events.

Common statistical Analysis

There are a few commonly used statistical methods: Mean, Median, Mode, Range, Standard deviation, Regression, and Hypothesis testing.

Mean: Mean is calculated as an average by summing up the list of numbers and dividing by the number of items. It is the most straightforward statistical tool for determining the central point of a data set, or in other words, it is the measure of central tendency. Mean is the average of the data set. Data can be grouped or ungrouped. The method of calculating the mean depends on the nature of the data. The mean can also be arithmetic or geometric.

Arithmetic Formula: Sum of the numbers in a set/total quantity of the numbers of the set.

Geometric Formula: Multiply all the data set values and take a root of the number.

Median: The median is the middle value in a data set. Usually, a data set has odd or even numbers, organized from the most minor to the largest. In the case of odd numbers, the middle number is the median. In the case of even numbers, an average of the middle two numbers is calculated and considered the median. The median is also the calculation of the average, hence known as the measure of central tendency.

Mode: Mode is the number that occurs the maximum number of times. The value that has the highest frequency in a given data set is the mode. If there are two modes in a given data set, it is called bimodal. If there are three modes in a given data set, it is called trimodal. If there are four or more than four modes in a given set, then it is called a multi-modal.

Range: In statistics, range is a measurement of a data set's spread. It is the variance between a data set's highest and lowest values. The range is a commonly used variance in statistics.

Standard deviation (SD): SD measures the variation of a random variable from the mean. A low SD indicates that the values are close to the mean, and a high standard deviation implies that the values are spread out over an extensive range away from the mean.

Regression: Regression relates a dependable variable to one or more independent variables. It depicts the changes in the observer's dependent variable when one or more independent variables change.

Hypothesis testing: In hypothesis testing, the population parameter assumptions are tested. There are two hypotheses: null hypothesis and alternative hypothesis.

Conclusion: Statistics is a vast subject and has several real-life applications. If you want to learn more about the topic, enroll in our statistics course.