Mastering Statistics for Machine Learning

Understand and apply basic statistical concepts to analyze data. Interpret and visualize data distributions. Calculate and interpret measures of central tendency and variability. Perform hypothesis testing and understand its importance in ML. Apply probability theory to model uncertainty in predictions. Understand and utilize correlation and regression techniques. Evaluate model performance using statistical metrics. Integrate statistical methods into machine learning workflows.

Instructors:

SJ Sushmitha J

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115 Lessons

This course provides a comprehensive introduction to the essential statistical concepts and techniques used in machine learning. Designed for beginners and professionals alike, it covers the fundamentals of descriptive statistics, probability, hypothesis testing, and inferential statistics. Through hands-on exercises and practical examples, you will learn how to analyze data, draw meaningful conclusions, and apply statistical methods to improve machine learning models. By the end of the course, you will be equipped with the skills to confidently use statistics as a powerful tool in their ML projects.

Course Content

Module 1,Mastering Statistics for Machine Learning

What is Statistics?

What is a Population in Statistics?

What is Descriptive Statistics vs Inferential Statistics?

Statistics Definitions - What is Mean, Median, Mode, Range & More

Frequency Distribution Table in Statistics Math and Science

Relative And Cumulative Frequency Distribution

Pie Charts, Bar Graphs, And Pareto Charts

What is a Histogram in Statistics?

Stem And Leaf Plots

Statistics Population Mean & Sample Mean

Calculating the Mean

Median and Mode in Statistics

Range of Data in Statistics

What is Variance in Statistics?

Calculating Variance in Statistics

Population and Sample Standard Deviation Calculation

Calculating Standard Deviation

What is Coefficient Of Variation?

Standard Deviation Of Data In A Frequency Table

Empirical Rule Of Standard Deviation

Standard Deviation Empirical Rule Problems in Statistics

Chebyshev's Theorem Explained

Quartiles Of Data Explained

Box And Whisker Plots in Statistics

Standard Score Z-Score Explained

Stem and Leaf Plots in Statistics

Module 2,Mastering Statistics for Machine Learning

Intro To This Course

Random Variables and Discrete Probability Distributions

The Normal Probability Distribution

Properties Of The Normal Distribution

The Area Under The Normal Distribution

The Standard Normal Distribution

Practice With Standard Normal Distributions

Using a z-Chart Table, Part 1

Using a z-Chart Table, Part 2

Using a z-Chart Table, Part 3

Using a z-Chart Table, Part 4

Finding Probability Using A Normal Distribution, Part 1

Finding Probability Using A Normal Distribution, Part 2

Finding Probability Using A Normal Distribution, Part 3

Finding Probability Using A Normal Distribution, Part 4

Finding Probability Using a Normal Distribution, Part 5

Finding Z-values With a Normal Distribution, Part 1

Finding Z-values With a Normal Distribution, Part 2

Finding Z-values With a Normal Distribution, Part 3

Finding Z-values With a Normal Distribution, Part 4

Area Under the Normal Probability Distribution - Statistics

Module 3,Mastering Statistics for Machine Learning

Sampling Distributions

What is the Central Limit Theorem in Statistics?

Central Limit Theorem, Part 2

Applying Central Limit Theorem To Population Means, Part 1

Applying Central Limit Theorem To Population Means, Part 2

Applying Central Limit Theorem To Population Means, Part 3

Applying Central Limit Theorem To Population Proportions, Part 1

Applying Central Limit Theorem To Population Proportions, Part 2

Confidence Intervals For Population Means, Part 1

Confidence Interval For Population Means, Part 2

Estimating Population Means large Samples, Part 1

Estimating Population Means large Samples, Part 2

Estimating Population Means large Samples, Part 3

The Student t-Distribution

Using A Student t-Distribution Statistical Table

Estimating Population Means small Samples, Part 1

Estimating Population Means small Samples, Part 2

Estimating Population Means small Samples, Part 3

Confidence Interval for Population Means in Statistics

Module 4,Mastering Statistics for Machine Learning

Estimating Population Proportions, Part 1

Estimating Population Proportions, Part 2

Estimating Population Proportions, Part 3

The Chi square Distribution

Estimating Population Variance, Part 1

Estimating Population Variance, Part 2

Estimating Population Variance, Part 3

Intro to Hypothesis Testing in Statistics - Hypothesis Testing

Null and Alternate Hypothesis - Statistical Hypothesis Testing

Rejection Regions In Hypothesis Testing

Hypothesis Testing For Means & Small Samples, Part 1

Hypothesis Testing For Means & Small Samples, Part 2

Hypothesis Testing For Means & Small Samples, Part 3

Hypothesis Testing For Means & Small Samples, Part 4

Hypothesis Testing For Means & Small Samples, Part 5

Hypothesis Testing For Means & Small Samples, Part 6

Hypothesis Testing For Means & Small Samples, Part 7

Hypothesis Testing For Means & Small Samples, Part 8

Module 5,Mastering Statistics for Machine Learning

Hypothesis Testing For Means & Large Samples, Part 1

Hypothesis Testing For Means & Large Samples, Part 2

Hypothesis Testing For Means & Large Samples, Part 3

Calculate the P-Value in Statistics - Formula to Find the P-Value in Hypothesis Testing

Using P-Values in Hypothesis Testing

Hypothesis Testing For Means Using P-values & Large Samples, Part 1

Hypothesis Testing For Means Using P-values & Large Samples, Part 2

Hypothesis Testing For Means Using P-values & Large Samples, Part 3

Hypothesis Testing For Means Using P-values & Large Samples, Part 4

Hypothesis Testing For Population Proportions, Part 1

Hypothesis Testing For Population Proportions, Part 2

Hypothesis Testing For Population Proportions, Part 3

Types Of Errors In Hypothesis Testing

Hypothesis Testing For Population Variance, Part 1

Hypothesis Testing For Population Variance, Part 2

Hypothesis Testing For Population Variance, Part 3

Hypothesis Testing For Population Variance, Part 4

Module 6,Mastering Statistics for Machine Learning

Hypothesis Testing - Two Means - Large Independent Samples, Part 1

Hypothesis Testing - Two Means - Large Independent Samples, Part 2

Hypothesis Testing - Two Means - Large Independent Samples, Part 3

Hypothesis Testing - Two Means - Large Independent Samples, Part 4

Hypothesis Testing - Two Means - Small Independent Samples, Part 1

Hypothesis Testing - Two Means - Small Independent Samples, Part 2

Hypothesis Testing - Two Means - Small Independent Samples, Part 3

Hypothesis Testing - Two Proportions - Large Independent Samples, Part 1

Hypothesis Testing - Two Proportions - Large Independent Samples, Part 2

Hypothesis Testing - Two Proportions - Large Independent Samples, Part 3

Hypothesis Testing - Two Means - Dependent Samples, Part 1

Hypothesis Testing - Two Means - Dependent Samples, Part 2

Hypothesis Testing - Two Means - Dependent Samples, Part 3

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