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Notes

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CIS

Discrete Structures

Graph Theory

Discrete Distributions

MATH

Adv Calc

Applications of Partial Derivatives

Convergence of Series

Critical Points

Directional Derivatives

Gradient Vector

Multi-variable Change of Variables

Multi-Variable Curves & Surfaces

Multi-variable Differential Calculus

Multi-variable Functions

Multi-variable Integration

Differential Equations

Autonomous DEs

Bernoulli Equations

DE solutions as series

Differential Equations

Second-Order Linear DEs

Separable DEs

Solution to DEs

Solutions to First-Order DEs

Standard form for linear DEs

Step Functions

Total Derivative

STATS

Cheatsheets

3100 Cheat Sheet

3110 Final Cheat Sheet

3110 Midterm Cheat Sheet

Intro to Stats

Bernoulli Distribution

Bernoulli Trials

Binomial Distribution

Central Limit Theorem

Chi-Squared Distribution

Chi-Squared Test

Coefficient of Determination

Combinatorial methods

Confidence Intervals

Continuous Normal Distributions

Descriptive Statistics

Experiments and Observational Studies

F distribution

Hypergeometric Distribution

Hypothesis Testing

Hypothesis Types

Inference for Proportions

Inference for two means

Negative Binomial Distribution

Normal Distribution

One-way ANOVA

P-values

Pearson Correlation Coefficient

Percentiles

Poisson Distribution

Population and Samples

Probabilities concepts

quantile-quantile plots (QQ plot)

Sample Proportion

Sampling Distributions

Simple Linear Regression

Math Stats 1

Conditional Distributions

Conditional Expectation

Conditional probability

Covariance

Discrete Uniform Distribution

Exponential Distribution

Gamma Distribution

Gamma function

Geometric Distribution

Independency

Marginal Distributions

Markov inequality

Mathematical Expectation

Moment Generating Functions

Moments of Linear Combinations

Moments

Multivariable Distributions

Probability Densities

Probability Distributions

Math Stats 2

Change of Random Variables

Chapter Guide

Consistency

Cramér-Rao inequality

Critical Region

Distribution function technique

Efficiency

Error types

Finding point estimators

Goodness of fit test

Interval estimation for mean

Interval estimation for proportions

Interval estimation for the difference between means

Interval estimation for the difference between proportions

Interval estimation for variances

Interval Estimation

Likelihood ratio test

Mean square error

Method of maximum likelihood

Method of moments (MM)

Multinomial Distribution

Power function of a test

Regularity

Sufficiency

Test function

Test of difference between means

Test of k proportions

Test of Means

Test of Proportions

Test of Variances

Transformation technique

Unbiasedness

Research

Expectation-Maximization Algorithm

Gaussian Finite Mixture Model

Generalized Linear model

Minorization-Maximization Algorithm

Penalized Likelihood

Stats 2

Multiple Linear Regression

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Markov inequality

$\forall k > 0 :$

P (X \geq k) \leq \frac{E (X)}{k} = \frac{μ}{k}

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