Statistics is the study of data collection, analysis, interpretation, presentation, and organizing in a specific way. Mathematical methods used for different analytics include mathematical analysis, linear algebra, stochastic analysis, the theory of measure-theoretical probability, and differential equation. Collecting, classifying, organizing, and displaying numerical data is associated with statistics. This helps one to grasp different outcomes from it and foresee several possibilities of various events. Statistics discuss information, observations, and data in the form of numerical data. We are able to find different indicators of central tendencies and the divergence of various values from the center with the help of statistics.
The ability to analyze and interpret statistical data is a vital skill for researchers and professionals from a wide variety of disciplines. You may need to make decisions on the basis of statistical data, interpret statistical data in research papers, do your own research, and interpret the data.
Types of Statistics
Statistics is mainly divided into the following two categories.
In the 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.
Data is typically arranged and displayed in tables or graphs summarizing details such as histograms, pie charts, bars or scatter plots.
Descriptive statistics are just descriptive and thus do not require generalization beyond the data collected.
In the Inferential Statistics, we try to interpret the meaning of descriptive statistics. After the data has been collected, analyzed, and summarised we use Inferential Statistics to describe the meaning of the collected data.
Inferential Statistics use the probability principle to assess whether trends contained in the research sample can be generalized to the larger population from which the sample originally comes.
Inferential Statistics are intended to test hypotheses and investigate relationships between variables and can be used to make population predictions.
Inferential Statistics are used to draw conclusions and inferences, i.e., to make valid generalizations from samples.
In a class, the data is the set of marks obtained by 50 students. Now when we take out the data average, the result is the average of 50 students’ marks. If the average marks obtained by 50 students are 88 out of 100, on the basis of the outcome, we will draw a conclusion.
Stages of Statistics
Collection of Data:
This is the first step of statistical analysis where we collect the data using different methods depending upon the case.
Organizing the Collected Data:
In the next step, we organize the collected data in a meaningful manner. All the data is made easier to understand.
Presentation of Data:
In the third step we simplify the data. These data are presented in the form of tables, graphs, and diagrams.
Analysis of the Data:
Analysis is required to get the right results. It is often carried out using measures of central tendencies, measures of dispersion, correlation, regression, and interpolation.
Interpretation of Data:
In this last stage, conclusions are enacted. Use of comparisons is made. On this basis, forecasting is made.
Uses of Statistics
Statistics helps to obtain appropriate quantitative data.
Statistics helps to present complex data for the simple and consistent interpretation of the data in a suitable tabular, diagrammatic, and graphic form.
Statistics help to explain the nature and pattern of variability through quantitative observations of a phenomenon.
Statistics help to depict the data in tabular form, or in a graphical form in order to understand it properly.
Applications of Statistics
Statistics is used in Machine Learning and Data Mining.
Statistics is used in Mathematics.
Statistics is used in Economics.