Lesson 3: Descriptive Statistics, Probability, and Distributions
Lesson Overview
Develop practical capability in descriptive statistics, probability, and distributions as part of the Essential Mathematics and Statistics for Machine Learning with MATLAB learning path.
Topics Covered
Mean, median, variance, standard deviation, and quantiles
Histograms, box plots, scatter plots, and distributions
Probability rules and conditional probability
Common discrete and continuous distributions
Sampling, random variables, and simulation
Correlation and covariance
Practical Activity
Build a guided MATLAB exercise covering mean, median, variance, standard deviation, and quantiles.
Apply histograms, box plots, scatter plots, and distributions to a practical engineering or data scenario.
Validate results and troubleshoot an issue involving correlation and covariance.
Key Takeaways
Explain and apply mean, median, variance, standard deviation, and quantiles.
Use probability rules and conditional probability in a structured workflow.
Validate outputs with plots, metrics, tests, or simulation evidence.
