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Probability & Statistical Inference Fundamentals

1. Probability Foundations

Probability Spaces

ConceptFormula
Sample space
Event
Probability measure
Normalization
Additivity

Conditional Probability & Independence

ConceptFormula
Conditional probability
Independence
Conditional independence
Bayes' rule

Random Variables

ConceptFormula
Random variable
Discrete PMF
Continuous PDF with
CDF

2. Expectation & Moments

Expectation

ConceptFormula
Expectation (discrete)
Expectation (continuous)
Linearity

Variance & Covariance

ConceptFormula
Variance
Alternate form
Covariance
Correlation

Laws

LawFormula
Total probability
Total expectation
Total variance

3. Common Distributions

Discrete

DistributionPMFMeanVariance
Bernoulli
Binomial
Poisson

Continuous

DistributionPDFMeanVariance
Uniform
Normal
Exponential

4. Inequalities & Concentration

InequalityStatement
Markov
Chebyshev
Hoeffding

5. Sampling & Limit Theorems

Laws of Large Numbers

TypeStatement
Weak LLN
Strong LLN

Central Limit Theorem

StatementFormula
CLT

6. Estimation Theory

Point Estimation

ConceptFormula
Sample mean
Sample variance
Bias
MSE

Likelihood & MLE

ConceptFormula
Likelihood
Log-likelihood
MLE

7. Confidence Intervals

Mean Estimation

CaseInterval
Known
Unknown

Variance Estimation

IntervalFormula
Variance CI

8. Hypothesis Testing

General Structure

StepDescription
Null hypothesis
Alternative
Test statisticFunction of data
Significance
DecisionReject / fail to reject

Common Tests

TestStatisticReference
Z-test
One-sample t
Two-sample tWelch
Chi-square

Errors & Power

ConceptDefinition
Type I errorReject true
Type II errorFail to reject false
Power
p-value