7.1 - Contingency Table: Marginal vs Conditional Distribution

A1) Mutually Exclusive vs Independent Events

A2) Conditional Probability Formula for Independent Events

A3) Law of Large Numbers (LLN)

A4) If you test positive for cancer, what is the probability that you in fact has cancer?

A5) Are Disjoint Events Independent?

B1) What is a Random Variable?

B2) Expected Value of a Random Variable

B3) Random Variable: Variance and Standard Deviation

B4) Prove that E(cX) = cE(X)

B5) Prove that Var(cX)=ccVar(X)

B6) Var(X)=E(X^2)-[E(X)]^2

B7) Bernoulli Random Variable

C1) Random Variables: Mean and Standard Deviation

C2) Covariance vs Variance

C3) Correlation vs Covariance

D1) Standard Normal Distribution

D2) What is z-score?

D3) What means independent and identically distributed (iid)?

E1) Population Parameter vs Sample Statistic

E2) Standard Error of the Mean

F1) 95% Confidence Interval for Proportion (p)

F2) Normal vs Student’s t-distribution

G1) Null vs Alternative Hypothesis

G2) Type I vs Type II Errors

H1) Randomized Experiment

H2) Two-Sample t-Test in Python

[graciecurran]

Thanks! I totally understand marginal vs conditional distribution now!

[rarissime_bey]

This 1min was better than my university 2hrs lecture.🥳