Ementorhub

What you'll learn

Learn to analyze relationships between random variables through joint probability distributions and independence concepts.

Understand how to calculate and interpret expected values, variances, and correlations for random variables.

Acquire essential skills in conducting statistical tests, including T-tests and confidence intervals, for data analysis.

Explore the principles of Markov chains and their applications in modeling systems with memoryless properties and calculating entropy.

Skills you'll gain

Statistical Hypothesis Testing

R Programming

Probability & Statistics

Statistical Modeling

Probability

Statistical Analysis

Statistical Inference

Probability Distribution

Data Analysis

Regression Analysis

Statistical Methods

Data Science

Markov Model

Statistics

Applied Mathematics

There are 6 modules in this course

Completing this course equips you with the skills to analyze complex data sets and make informed predictions, enhancing your proficiency in statistical reasoning and inference. Unique to this course is its blend of theoretical foundations and practical applications, ensuring that you can not only understand the principles but also implement them using tools like R. Whether you're pursuing a career in data science, machine learning, or any data-centric discipline, this course will empower you to tackle challenging statistical problems and drive meaningful insights from data.

Joint Distributed Random Variables

Expectation

Inequalities and Central Limit Theorem

Statistical Testing

Markov Chain