## Overview of Probability Tutorial

There is not even a single day in your life when you don’t think about using probability and statistics. Deciding between two options, making predictions, learning weather forecasts, and creating hypotheses are all important aspects of probability. Our daily routines revolve around probability, and statistics is the next significant discipline that governs and determines much of our probable results. Probability and statistics are related yet independent fields.

Statistical Analysis uses probability distributions and theories to make any data calculations and present it via graphs, charts, and pictographs. The two disciplines are learned together to receive meaningful and relevant output in a business. They can serve many purposes from analyzing huge volumes of data, and organizing it to present it in the simplest graphical manner.

Whether you belong to the field of Data Science, Big data Analysis, or Business Intelligence, learning statistics and probability can be of great help to improve business performance, handle and exhibit the data available and apply various logical algorithms, functions, and methods on that data.

**Check out our blog for a detailed comparison of Data Mining and Statistics.**

In this tutorial, we will cover a range of topics that are going to refurbish your mathematics, statistics and probability knowledge from school and college times. Further, individuals and statisticians who are willing to enhance The topics include descriptive statistics that will describe varying data through various distributions. You will also get familiar with grouped frequencies, graphical descriptions, probability distributions of discrete and continuous variables, The Normal Distribute (most important of all distributions) and Sampling and Combination of variables.

Most topics here contain explanations relating to mathematical interest to keep up your attention and concentration towards learning. As we say, science, technology and mathematics are directly proportional to practice and practical implementation, each topic in this learning reference is thoroughly explained using real-time examples, which are easy-to-comprehend and memorize.

After learning through this Probability tutorial, you can also enroll in our Data Science courses. These courses are excellently descriptive and provide deeper insights into significant topics, which can be implemented in real-time projects in your organization.

**Recommended Audience for this Probability Tutorial**

- Professionals who want to build their career in Data Science
- Project Managers responsible for decision-making, research work in the organization
- Marketing Managers who are responsible for fetching data and building reports
- Data Scientists to have a thorough knowledge of Statistics and Probability
- Graduates from all disciplines like Science, Commerce, Arts and others
- Undergraduates and School students who want to enhance their Mathematical concepts of stats and probability

**Probability Tutorial Prerequisites**

- Strong and quick in mathematical calculations can be beneficial

Learn more about ** SAS** in this insightful blog now!

Never thought prob can be that simple. thanks for sharing such a informative material..

Good tutorial..thank you so much. keep up the good work.