Statistics

Statistics is the study of data collection, analysis, perception, introduction, and organization. It is a method of gathering and summarizing results. This has a wide range of uses, from small to large. Stats are used for any data collection, whether it is the study of the country’s population or its economy.

Statistics has a wide range of applications in many disciplines, including economics, psychology, geology, weather forecasts, and so on. The information gathered for research here may be quantitative or qualitative. Quantitative data can also be divided into two types: discrete and continuous. Continuous data has a spectrum rather than a single value, whereas discrete data has a fixed value.

Table of Contents

1. Statistical Data
2. Statistical Methods

Statistical Data

When complete census data cannot be obtained, statisticians gather sample data through the creation of complex experiment designs and survey samples. Statistics, in and of itself, offers tools for prediction and forecasting via statistical models. The scientific discipline of probability theory includes sampling theory. In mathematical statistics, the probability is used to investigate the sampling distributions of sample statistics and, more broadly, the properties of statistical procedures like organizing and grouping data through graphs, pie charts, etc as discussed in the articles below:

1. Data Handling
2. Organizing Data
3. Grouping Data
4. Pie Chart
5. Chance and Probability
6. Introduction to Graphs
7. Linear Graphs
8. Presentation of data
9. Graphical representation of Data
10. Bar graphs and Histograms

Statistical Methods

Any statistical method is accurate whether the structure or population under consideration meets the method’s assumptions. The fundamental distinction between classical probability theory and sampling theory is that probability theory begins with the given parameters of a total population and deduces probabilities that apply to samples. Statistical inference, on the other hand, proceeds in the other way, inferring from samples to the parameters of a greater or entire population. Let’s discuss the statistical methods as:

1. Central Tendency
2. Mean, Median, Mode, and Range
3. Step deviation Method for Finding the Mean with Examples
4. Mean, Median, and Mode of a grouped data
5. Cumulative Frequency Curve
6. Measures of Spread
7. Mean Absolute Deviation
8. Measures of Central Tendency
9. Difference Between Mean, Median, and Mode with Examples
10. Analysis of Frequency Distribution
11. Variance and Standard Deviation