Skip to main content
grasp.study
About
Explore
Pricing
Log in
Try it for free
Back to course
👋
Welcome to a Grasp lesson
Create a free account
to keep studying and create your own study path.
Introduction to Data Science (DS 215)
·
Module 2
Probability Models for Data
1
Implementing Probability Distributions with SciPy
Review and implement key probability distributions (e.g., Gaussian, Poisson, Binomial) using SciPy.
2
PDFs of Transformed Random Variables: Jacobian Method
Derive the PDF of a transformed random variable using the Jacobian method.
3
Markov and Chebyshev Inequalities: Proofs and Applications
Prove Markov's and Chebyshev's inequalities from first principles and explain their application.
4
Covariance and Correlation of Linear Combinations
Derive the covariance and correlation of linear combinations of random variables.
5
Visualizing Probability: A Geometric Approach
Construct intuitive geometric explanations for joint, marginal, and conditional probability distributions.
Previous module
The Data Scientist's Python Toolkit
Next module
Asymptotic Theory and Simulation