MATH 230 • Midterm • Probability and Statistics for Engineering
Mühendisliğin sayısal temellerini attığımız bu derste soru okyanusu içerisinden özenle seçilmiş çözümlü soru örnekleri ve hedefe yönelik konu anlatımlarıyla işin çok kolay!
Eğitmenler
İhsan Altundağ
Eğitmen
2007 yılında Galatasaray Üniversitesi Bilgisayar Mühendisliği bölümünden birincilikle mezun olduktan sonra Fransa'da Kriptoloji üzerine Fransa hükümeti tarafından verilen bursla yüksek lisans yaptım. Devamında ikinci kez sınava girerek Boğaziçi Matematik bölümünü de bitirdim. Yaklaşık 15 yıldır üniversite öğrencilerine dersler vermekteyim.
Ömer Faruk Altun
Co-founder & Head of Education
2011 yılında Endüstri Mühendisliği okumak için başladığım Sabancı Üniversitesi'nden 2018 yılında Bilgisayar Mühendisi olarak mezun oldum. 13 yıldır Altun ismiyle başta Sabancı Üniversitesi olmak üzere çeşitli okullarda Endüstri ve Bilgisayar Mühendisliği alanlarında ders vermekteyim. Unicourse'ta sunduğum derslerin yanında eğitim departmanının da sorumluluğunu üstlenmekteyim.
Paketi Tamamla
🎓 Bilkent Üniversitesinde öğrencilerin %92'si tüm paketi alarak çalışıyor.
Konular
Counting
Basic Principles of Counting
Counting Examples
Permutations
Permutations Example
Groups and Circular Permutation Example
Identical Objects Example 1
Identical Objects Example 2
Identical Objects Example 3
Combination
n choose r
Committee Example 1
Committee Example 2
Ball Example 1
Ball Example 2
Axioms of Probability
Sample Space and Events
Probability
Axioms of Probability
Some Rules
Coin Example
Dice Example
Card Example 1
Card Example 2
Ball Example
Set Example
Birthday Example
Conditional Probability, Independence
Conditioning Events
Total Probability Rule
Example 1
Example 2
Example 3
Example 4
Example 5
Example 6
Independence
Independence Example 1
Independence Example 2
Sample Midterm Problems I
Counting 1
Counting 2
Counting 3
Counting 4
Axioms of Probability 1
Axioms of Probability 2
Axioms of Probability 3
Axioms of Probability 4
Conditional Probability 1
Conditional Probability 2
Conditional Probability 3
Conditional Probability 4
Independence 1
Independence 2
Conditional Probability and Independence
Discrete Random Variables
Random Variables
Probability Mass Function
PMF Example 1
PMF Example 2
Cumulative Distribution Function
CDF Example 1
Expected Value
Expected Value Example 1
Expected Value Example 2
Variance
Variance Example 1
Variance Example 2
Special Discrete Distributions
Bernoulli Distribution - 1
Bernoulli Distribution - 2
Example 1
Binomial Distribution - 1
Binomial Distribution - 2
Example 2
Example 3
Negative Binomial Distribution - 1
Negative Binomial Distribution - 2
Example 4
Hypergeometric Distribution
Example 5
Poisson Distribution - 1
Poisson Distribution - 2
Example 6
Example 7
Poisson Approximation to Binomial Distribution
Example 8
Geometric Distribution Part 1
Geometric Distribution Part 2
Example 1
Example 2
Sample Midterm Problems II
Discrete Random Variables 1
Discrete Random Variables 2
Discrete Random Variables 3
Discrete Random Variables 4
Discrete Random Variables 5
Discrete Random Variables 6
Discrete Random Variable 7
Discrete Random Variables 8
Discrete Random Variable 9
Binomial Distribution 1
Binomial Distribution 2
Binomial Distribution 3
Binomial Distribution 4
Poisson distribution 1
Poisson Distribution 2
Poisson Distribution 3
Poisson distribution 4
Hypergeometric Distribution 1
Hypergeometric Distribution 2
Hypergeometric Distribution 3
Negative Binomial Distribution 1
Negative Binomial - Geometric Distribution
Geometric Distribution 1
Geometric Distribution 2
Geometric Distribution 3
Continuous Random Variables
Probability Density Function - PDF
Example 1
Cumulative Distribution Function - CDF
Example 2
Expected Value
Expected Value - Example 1
Expected Value - Example 2
Variance
Variance - Example 1
Special Continous Distributions
Uniform Distribution
Example 1
Example 2
Exponential Distribution
Example 3
Example 4
Memoryless Property
Example 5
Normal Distribution (Gaussian Distribution)
Standard Normal Distribution
Reading Z Table - Option 1
Reading Z Table - Option 2
Example 6
Gamma Distribution
Example 8
Relation of Gamma Distribution with Others
Moment Generating Functions
Introduction
Formulas
Properties
Example 1
Example 2
Example 3
Example 4
Example 5
Sample Midterm Problems III
Continuous Random Variables 1
Continuous Random Variables 2
Continuous Random Variables 3
Continuous Random Variables 4
Continuous Random Variables 5
Continuous Random Variables 6
Uniform Distribution 1
Uniform Distribution 2
Exponential Distribution 1
Exponential Distribution 2
Exponential Distribution 3
Exponential Distribution 4
Exponential Distribution 5
Normal Distribution 1
Normal Distribution 2
Normal Distribution 3
Normal Distribution 4
Normal Distribution 5
Normal Distribution 6
Normal Distribution 7
Moment Generating Function 1
Moment Generating Function 2
Moment Generating Function 3
Moment Generating Function 4
Moment Generating Function 5
Spring 25 Midterm
Expected Value - Discrete Random Variable
Binomial and Geometric Distributions
Continuous Random Variable
Poisson Distribution
Değerlendirmeler
Ders İçeriği
Counting
Basic Principles of Counting
Counting Examples
Permutations
Permutations Example
Groups and Circular Permutation Example
Identical Objects Example 1
Identical Objects Example 2
Identical Objects Example 3
Combination
n choose r
Committee Example 1
Committee Example 2
Ball Example 1
Ball Example 2
Axioms of Probability
Sample Space and Events
Probability
Axioms of Probability
Some Rules
Coin Example
Dice Example
Card Example 1
Card Example 2
Ball Example
Set Example
Birthday Example
Conditional Probability, Independence
Conditioning Events
Total Probability Rule
Example 1
Example 2
Example 3
Example 4
Example 5
Example 6
Independence
Independence Example 1
Independence Example 2
Sample Midterm Problems I
Counting 1
Counting 2
Counting 3
Counting 4
Axioms of Probability 1
Axioms of Probability 2
Axioms of Probability 3
Axioms of Probability 4
Conditional Probability 1
Conditional Probability 2
Conditional Probability 3
Conditional Probability 4
Independence 1
Independence 2
Conditional Probability and Independence
Discrete Random Variables
Random Variables
Probability Mass Function
PMF Example 1
PMF Example 2
Cumulative Distribution Function
CDF Example 1
Expected Value
Expected Value Example 1
Expected Value Example 2
Variance
Variance Example 1
Variance Example 2
Special Discrete Distributions
Bernoulli Distribution - 1
Bernoulli Distribution - 2
Example 1
Binomial Distribution - 1
Binomial Distribution - 2
Example 2
Example 3
Negative Binomial Distribution - 1
Negative Binomial Distribution - 2
Example 4
Hypergeometric Distribution
Example 5
Poisson Distribution - 1
Poisson Distribution - 2
Example 6
Example 7
Poisson Approximation to Binomial Distribution
Example 8
Geometric Distribution Part 1
Geometric Distribution Part 2
Example 1
Example 2
Sample Midterm Problems II
Discrete Random Variables 1
Discrete Random Variables 2
Discrete Random Variables 3
Discrete Random Variables 4
Discrete Random Variables 5
Discrete Random Variables 6
Discrete Random Variable 7
Discrete Random Variables 8
Discrete Random Variable 9
Binomial Distribution 1
Binomial Distribution 2
Binomial Distribution 3
Binomial Distribution 4
Poisson distribution 1
Poisson Distribution 2
Poisson Distribution 3
Poisson distribution 4
Hypergeometric Distribution 1
Hypergeometric Distribution 2
Hypergeometric Distribution 3
Negative Binomial Distribution 1
Negative Binomial - Geometric Distribution
Geometric Distribution 1
Geometric Distribution 2
Geometric Distribution 3
Continuous Random Variables
Probability Density Function - PDF
Example 1
Cumulative Distribution Function - CDF
Example 2
Expected Value
Expected Value - Example 1
Expected Value - Example 2
Variance
Variance - Example 1
Special Continous Distributions
Uniform Distribution
Example 1
Example 2
Exponential Distribution
Example 3
Example 4
Memoryless Property
Example 5
Normal Distribution (Gaussian Distribution)
Standard Normal Distribution
Reading Z Table - Option 1
Reading Z Table - Option 2
Example 6
Gamma Distribution
Example 8
Relation of Gamma Distribution with Others
Moment Generating Functions
Introduction
Formulas
Properties
Example 1
Example 2
Example 3
Example 4
Example 5
Sample Midterm Problems III
Continuous Random Variables 1
Continuous Random Variables 2
Continuous Random Variables 3
Continuous Random Variables 4
Continuous Random Variables 5
Continuous Random Variables 6
Uniform Distribution 1
Uniform Distribution 2
Exponential Distribution 1
Exponential Distribution 2
Exponential Distribution 3
Exponential Distribution 4
Exponential Distribution 5
Normal Distribution 1
Normal Distribution 2
Normal Distribution 3
Normal Distribution 4
Normal Distribution 5
Normal Distribution 6
Normal Distribution 7
Moment Generating Function 1
Moment Generating Function 2
Moment Generating Function 3
Moment Generating Function 4
Moment Generating Function 5
Spring 25 Midterm
Expected Value - Discrete Random Variable
Binomial and Geometric Distributions
Continuous Random Variable
Poisson Distribution
Sıkça Sorulan Sorular
Örneğin, Koç Üniversitesi - MATH 101 (Calculus) veya başka bir okulun benzer dersi olsun, paketlerimiz tam da o derse göre tasarlanır. Böylece nokta atışı çalışır, zaman kazanırsın.
Sınava özel videolar —konu anlatımları, çıkmış sorular ve çözümleri, özet notlar—içerir. Sınavda sıkça çıkan soruları hedefler. Eğitmenlerimiz, üniversitenin akademik takvimini takip ederek paketleri sürekli günceller. Böylece, gereksiz detaylarla vakit kaybetmeden başarını artırmaya odaklanabilirsin.