Essential Statistics for Data Science - Learn Statistics for Data Science

Learn about the Essential Statistics for Data Science! If you want to foray into the world of data science, you need to have a good command of statistics. Statistical knowledge helps us use the proper methods to collect the data, employ the correct analysis, and effectively present the results. Statistics is a crucial process for making discoveries in science, make decisions based on data and making predictions.

Great Learning brings you this intensive course on “Essential Statistics for Data Science” which will help you to comprehensively learn all necessary topics essential in statistics for Data Science. This in-depth course starts by discussing the measures of central tendency and deviation followed by stats concepts in Python. Then, the course discusses the normal distribution empirical rule and hypothesis testing. Finally, we understand the ANOVA and Chi-square test. This video teaches these concepts in detail to help you learn essential statistics for data science on the right note.

➤ Skip Intro: .
Introduction.
Measures of Central Tendency and Deviation.
Central Limit Theorem.
Stats Concepts in Python.
Normal Distribution Empirical Rule.
Hypothesis Testing.
ANOVA.
Chi-Square Test.