Probability  Computer Science 3
Responsible  Lorcan Camps 

Last Update  24/02/2022 
Completion Time  3 days 6 hours 29 minutes 
Members  3 
Advanced
Technical
Computer Science

Probability

Probability explained  Independent and dependent events  Probability and Statistics  Khan Academy

Probability with playing cards and Venn diagrams  Probability and Statistics  Khan Academy

Addition rule for probability  Probability and Statistics  Khan Academy

Finding probability example 2  Probability and Statistics  Khan Academy

Compound probability of independent events  Probability and Statistics  Khan Academy

Coin flipping probability  Probability and Statistics  Khan Academy

Probability without equally likely events  Probability and Statistics  Khan Academy

Getting exactly two heads (combinatorics)  Probability and Statistics  Khan Academy

Exactly three heads in five flips  Probability and Statistics  Khan Academy

Frequency stability property short film  Computer Science  Khan Academy

Generalizing with binomial coefficients (bit advanced)  Probability and Statistics  Khan Academy

Probability (part 2)

Probability (part 3)

Probability (part 4)

Probability (part 5)

Probability (part 6)

Dependent probability example  Probability and Statistics  Khan Academy

Dependent probability example 2  Probability and Statistics  Khan Academy

Probability (part 7)

Probability (part 8)

Permutations

Combinations

Probability using combinations  Probability and Statistics  Khan Academy

Probability and combinations (part 2)  Probability and Statistics  Khan Academy

Conditional probability and combinations  Probability and Statistics  Khan Academy

Birthday probability problem  Probability and Statistics  Khan Academy

Introduction to Random Variables

Probability density functions  Probability and Statistics  Khan Academy

Binomial Distribution 1

Binomial Distribution 2

Binomial Distribution 3

Binomial Distribution 4

Expected Value: E(X)

Expected value of binomial distribution  Probability and Statistics  Khan Academy

Poisson process 1  Probability and Statistics  Khan Academy

Poisson process 2  Probability and Statistics  Khan Academy

Law of large numbers  Probability and Statistics  Khan Academy

Term life insurance and death probability  Finance & Capital Markets  Khan Academy

Mega millions jackpot probability  Probability and combinatorics  Precalculus  Khan Academy

Free throwing probability  Probability and Statistics  Khan Academy

Three pointer vs free throwing probability  Probability and Statistics  Khan Academy


Statistics

Statistics Lecture 1.1: The Key Words and Definitions For Elementary Statistics

Statistics Lecture 1.3: Exploring Categories of Data, Levels of Measurement

Statistics Lecture 1.5: Sampling Techniques. How to Develop a Random Sample

Statistics Lecture 2.2: Creating Frequency Distribution and Histograms

Statistics Lecture 3.2: Finding the Center of a Data Set. Mean, Median, Mode

Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set

Statistics Lecture 3.4: Finding ZScore, Percentiles and Quartiles, and Comparing Standard Deviation

Statistics Lecture 4.2: Introduction to Probability

Statistics Lecture 4.3: The Addition Rule for Probability

Statistics Lecture 4.4: The Multiplication Rule for "And" Probabilities.

Statistics Lecture 4.5: Probability of Complementary Events with "At Least One"

Statistics Lecture 4.7: Fundamental Counting Rule, Permutations and Combinations

Statistics Lecture 5.2: A Study of Probability Distributions, Mean, and Standard Deviation

Statistics Lecture 5.3: A Study of Binomial Probability Distributions

Statistics Lecture 5.4: Finding Mean and Standard Deviation of a Binomial Probability Distribution

Statistics Lecture 6.2: Introduction to the Normal Distribution and Continuous Random Variables

Statistics Lecture 6.3: The Standard Normal Distribution. Using zscore, Standard Score

Statistics Lecture 6.4: Sampling Distributions Statistics. Using Samples to Approx. Populations

Statistics Lecture 6.5: The Central Limit Theorem for Statistics. Using zscore, Standard Score

Statistics Lecture 7.2: Finding Confidence Intervals for the Population Proportion

Statistics Lecture 7.3: Confidence Interval for the Sample Mean, Population Std Dev  Known

Statistics Lecture 7.4: Confidence Interval for the Sample Mean, Population Std Dev  Unknown

Statistics Lecture 7.5: Confidence Intervals for Variance and Std Dev. ChiSquared Distribution.

Statistics Lecture 8.2: An Introduction to Hypothesis Testing

Statistics Lecture 8.3: Hypothesis Testing for Population Proportion

Statistics Lecture 8.4: Hypothesis Testing for Population Mean. Population Std Dev is Known.

Statistics Lecture 8.5: Hypothesis Testing for Population Mean. Population Std Dev is Unknown.

Statistics Lecture 8.6: Hypothesis Testing Involving Variance and Standard Deviation.


Algorithms and data structures

Java Algorithms

Java Sort Algorithm

Stacks and Queues

Linked List in Java

Linked List in Java 2

Java Recursion

Java Shell Sort

Java Quick Sort

Big O Notations

Java Hash Table

Java Hash Tables 2

Java Hash Tables 3

Java Binary Search Tree

Java Binary Search Tree 2

Solving Programming Problems

Solving Programming Problems 2

Java Heaps

Welcome to Data Structures

Complexity 1 Introduction to complexity

Complexity 2 Big Oh Notation

Complexity 3 Some examples of bigOh notation

Java 1 ObjectOrientedProgramming

Java 2 ComparableGenerics

Java 3 Introduction to Generic Programming

Java 4 Parameterized Types

Java 5 Autoboxing

Java 6 Exceptions

LinkedList 1 Introduction

LinkedList 2 Nodes and Size

LinkedList 3 Boundary Conditions

LinkedList 4 addFirst()

LinkedList 5 addLast()

LinkedList 6 removeFirst()

LinkedList 7 removeLast()

LinkedList 8 remove and find

LinkedList 9 peek()

LinkedList 10 Testing the list

LinkedList 11 Iterators

LinkedList 12 Double Linked Lists

LinkedList 13 Circular Linked Lists

Stacks and Queues 3 Using arrays to write stacks and queues

Hashes 1 Introduction

Hashes 2 Hash Functions

Hashes 3 Collisions

Hashes 4 Hash Functions for Strings

Hashes 5 Compressing numbers to fit the size of the array

Hashes 6 Make an integer positive

Hashes 7 LoadFactor()

Hashes 8 Open Addressing

Hashes 9 Chaining

Hashes 10 Rehashing

Hashes 11 the hash class

Hashes 12 Review of the hash element inner class

Hashes 13 Constructor for a chained hash.

Hashes 14 Review of constructors

Hashes 15 add() and remove() methods

Hashes 16 getValue()

Hashes 17 resize

Hashes 18 KeyIterator

Trees and heaps 1 Introduction

Heaps 1 Introduction and Tree levels

Heaps 2 Add Remove

Heaps 3 TrickleUp

Heaps 4 TrickleDown

Heaps 5 HeapSort

Trees 2 Complete and Full

Trees 3 Traversal

Trees 4 Expression Trees

Trees 5 Node Class

Trees 6 recursive add

Trees 7 Contains

Trees 8 Remove

Trees 9 Introduction to rotations

Trees 10 Rotations

Trees 11 Coding Rotations

AVL 1 Introduction

AVL Tree 2 Nodes

AVL Tree 3 Adding a node

AVL Tree 4 recursive add for an AVL tree

AVL Tree 5 checking balance in an AVL tree

AVL Tree 6 Rebalancing AVL trees

AVL Tree 7 complete example of adding data to an AVL tree.

Red Black Tree 1 The Rules

Red Black Trees 2 Example of building a tree

Red Black Tree 3  Classes

Red Black Tree 4  Add methods

Red Black Tree 5 checking violations in the tree

Red Black Tree 6 The Rotate method

Red Black Tree 7 left rotate

Red Black Tree 8 leftRightRotate

Red Black Tree 9 height

Red Black Tree 10 number of black nodes

Sorts 1 Introduction to sorts

Sorts 2 Selection Sort

Sorts 3 Insertion Sort

Sorts 4 Insertion Sort Code

Sorts 5 Shell Sort

Sorts 6 Merge Sort

Sorts 7 Merge Sort Code

Sorts 8 Quick Sort

Sorts 9 Quick Sort Worst Case

Sorts 10 Quick Sort Code

Sorts 11 Radix Sort

Sorts 12 Sort Summary

Bloom Filters

kmer algorithms: Compare and Swap

Data Structures Easy to Advanced Course  Full Tutorial from a Google Engineer


Intro to clientside development

Learn JavaScript  Full Course for Beginners


Linear algebra

Linear Algebra 1.1.1 Systems of Linear Equations

Linear Algebra 1.1.2 Solve Systems of Linear Equations in Augmented Matrices Using Row Operations

Linear Algebra 1.2.1 Row Reduction and Echelon Forms

Linear Algebra 1.2.2 Solution Sets and Free Variables

Linear Algebra 1.3.1 Vector Equations

Linear Algebra 1.3.2 Linear Combinations

Linear Algebra 1.4.1 The Matrix Equation Ax=b

Linear Algebra 1.4.2 Computation of Ax

Linear Algebra 1.5.1 Homogeneous System Solutions

Linear Algebra 1.5.2 NonHomogeneous System Solutions

Linear Algebra 1.6.1 Applications of Linear Systems  Economic Sectors

Linear Algebra 1.6.2 Applications of Linear Systems  Network Flow

Linear Algebra 1.7.1 Linear Independence

Linear Algebra 1.7.2 Special Ways to Determine Linear Independence

Linear Algebra 1.8.1 Matrix Transformations

Linear Algebra 1.8.2 Introduction to Linear Transformations

Linear Algebra 2.1.1 Matrix Operations  Sums and Scalar Multiples

Linear Algebra 2.1.2 Matrix Operations  Multiplication and Transpose

Linear Algebra 2.2.1 The Inverse of a Matrix

Linear Algebra 2.2.2 Solving 2x2 Systems with the Inverse and Inverse Properties

Linear Algebra 2.2.3 Elementary Matrices And An Algorithm for Finding A Inverse

Linear Algebra 2.3.1 Characterizations of Invertible Matrices

Linear Algebra 3.1.1 Introduction to Determinants

Linear Algebra 3.1.2 Cofactor Expansion

Linear Algebra 3.2.1 Properties of Determinants

Linear Algebra 4.1.1 Vector Spaces

Linear Algebra 4.1.2 Subspace of a Vector Space

Linear Algebra 4.2.1 Null Spaces

Linear Algebra 4.2.2 Column Spaces

Linear Algebra 4.3.1 Linearly Independent Sets and Bases

Linear Algebra 4.3.2 The Spanning Set Theorem

Linear Algebra 4.5.1 The Dimension of a Vector Space

Linear Algebra 4.5.2 Subspaces of a Finite Dimensional Space

Linear Algebra 4.6.1 The Row Space

Linear Algebra 4.6.2 Rank

Linear Algebra 5.1.1 Eigenvectors and Eigenvalues

Linear Algebra 5.1.2 More About Eigenvectors and Eigenvalues

Linear Algebra 5.2.1 Determinants and the IMT

Linear Algebra 5.2.2 The Characteristic Equation

Linear Algebra 6.1.1 Inner Product, Vector Length and Distance

Linear Algebra 6.1.2 Orthogonal Vectors

Linear Algebra 6.2.1 Orthogonal Sets

Linear Algebra 6.2.2 Orthogonal Projections

Linear Algebra 6.3.1 Orthogonal Decomposition Theorem

Linear Algebra 6.3.2 The Best Approximation Theorem

Linear Algebra 6.5.1 Least Squares Problems
