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Basics of Inferential Statistics

This data analytics course will help you learn how to use a random sample data to describe and make inference about the population. You will learn probability, statistics, continuous and discrete probability distributions, sampling methods and their error quantification and central limit theorem.

Program Overview

Key Highlights

Free and shareable certificate on completion
Free and shareable certificate on completion
Real time upskilling
Real time upskilling
15 hrs short course
15 hrs short course
100% self paced course
100% self paced course
Syllabus: Introduction to Probability, Discreete Probability Distributions, Binomial and Cumulated Disctribution, Continuous Probability Distribution, Central Limit Theorem, Properties of Sampling Distributions, Types of Sampling Methods, Applications of Sampling Methods, Concept of Bayes' Theorem
Syllabus: Introduction to Probability, Discreete Probability Distributions, Binomial and Cumulated Disctribution, Continuous Probability Distribution, Central Limit Theorem, Properties of Sampling Distributions, Types of Sampling Methods, Applications of Sampling Methods, Concept of Bayes' Theorem
Skills you will gain: Data Analytics, Basics of Probability, Problem Solving Skills, Probability Distributions, Center Limit Theorem, Applications of Sampling Methods
Skills you will gain: Data Analytics, Basics of Probability, Problem Solving Skills, Probability Distributions, Center Limit Theorem, Applications of Sampling Methods

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Certification

Basics of Inferential Statistics
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Basics of Inferential Statistics
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