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Probability and Statistics: Complete Course 2024

Learn the Probability and Statistics You Need to Succeed in Data Science and Business Analytics

     
  • 4.6
  •  |
  • Reviews ( 320 )
₹799

This Course Includes

  • iconudemy
  • icon4.6 (320 reviews )
  • icon16.5 total hours
  • iconenglish
  • iconOnline - Self Paced
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  • iconUdemy

About Probability and Statistics: Complete Course 2024

This is course designed to take you from beginner to expert in probability and statistics. It is designed to be practical, hands on and suitable for anyone who wants to use statistics in data science, business analytics or any other field to make better informed decisions.

Videos packed with worked examples and explanations so you never get lost, and every technique covered is implemented in Microsoft Excel so that you can put it to use immediately.

Key concepts taught in the course are:

Descriptive Statistics: Averages, measures of spread, correlation and much more.

Cleaning Data: Identifying and removing outliers

Visualization of Data: All standard techniques for visualizing data, embedded in Excel.

Probability: Independent Events, conditional probability and Bayesian statistics.

Discrete Distributions: Binomial, Poisson, expectation and variance and approximations.

Continuous Distributions: The Normal distribution, the central limit theorem and continuous random variables.

Hypothesis Tests: Using binomial, Poisson and normal distributions, T-tests and confidence intervals.

Regression: Linear regression analysis, correlation, testing for correlation, non-linear regression models.

Quality of Tests: Type I and Type II errors, power and size, p-hacking.

Chi-Squared Tests: The chi-squared distribution and how to use it to test for association and goodness of fit.

Much, much more!

It requires no prior knowledge, with the exception of 2 optional videos at the end of the continuous distribution chapter, in which knowledge of calculus is required).

What You Will Learn?

  • Descriptive Statistics.
  • Visualizing Data.
  • Probability Theory.
  • Bayesian Statistics.
  • Discrete Distributions (Binomial, Poisson and More).
  • Continuous Distributions (Normal and Others).
  • Hypothesis Tests.
  • Regression.
  • Type I and Type II Errors.
  • Chi-Squared Test.