Full Data Science Course: From Zero to Hero | Udemy


Full Data Science Course: From Zero to Hero | Udemy
English | Size: 340.98 MB
Genre: eLearning

Learn and build projects with Inferential Statistics

What you’ll learn
Learn the Main Concepts of Inferential Statistics
Calculate Parameters using Advanced Statistics Techniques
Reach conclusions using Hypothesis Testing
Calculate Confidence Intervals
Calculate ANOVAS: 1-Way and 2-Way
Calculate Estimators using MME, MLE, OLS

In this course, you will take the first step in your Data Science journey by learning Inferential Statistics.

Data Science Professionals in Machine Learning, Artificial Intelligence, and all professionals in several fields like Finance, Psychology, and the Medical Field, all require an understanding of Statistics. It is the core language of all these fields when it comes to Data Analysis.

You will be able to understand and master Machine Learning concepts when you understand the key foundations behind them. These come from mastering: Statistics and Mathematical Modelling.

Course Outline:

1. Master the Inferential Statistics Terminology and Concepts

Random Variables, Random Samples, the 4 types of Data, NOIR, Experiments vs Trials and Events.

2. Master the Discrete and Continuous Distributions and their Sub-Functions so you can know when and how to use them

Binomial, Bernoulli, Negative Binomial, Geometric, Poisson, Exponential, Uniform, Normal, T-Student, Chi-Squared, and F-Distribution.

3. Master Conversions from any Distribution to the Normal Distribution

From N to Z, from T to Z, from Chi-Squared to Z

4. Learn how to conduct Hypothesis Tests

1-Tailed and 2-Tailed, how to use any Statistical Table, Find Critical Values, compare to calculated test statistics, and make Conclusions.

5. Learn how to indicate conclusions based on percentages.

6. Learn how to build Confidence Intervals for a Population Parameter

7. Learn how to calculate Population Estimators using Advanced Statistics Techniques 

Ordinary Least Squares (OLS), Method of Moments Estimator (MME), and Maximum Likelihood Estimator(MLE)

Who this course is for:

  • Beginner Data Science students and professionals

Who this course is for:
Beginner Data Science students and professionals

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