# ENGR 240 (Spring 24) • Probability and Statistics for Engineers and Scientists • Midterm

Bu ders ile ENGR 240 sınavı için temel konseptleri çok iyi anlamakla kalmayıp sınava girmeye de tamamen hazır olacaksın.

Dersin içeriğinde yer alan Axioms of Probability, Conditional Probability, Independence, Bayes Theorem, Random Variable, PDF, CDF, Expected Value, Variance, Binomial Distribution ve Poisson Distribution kavramlarını çok iyi öğreneceksin ve hepsine dair en az birer örnek soru göreceksin.

## Konular

Ders Tanıtımı

Axioms of Probability 1

Ücretsiz

Axioms of Probability 2

Ücretsiz

Axioms of Probability 3

Ücretsiz

Axioms of Probability 4

Intuition of Conditional Probability

Conditional Probability 1

Conditional Probability 2

Conditional Probability and Sets

Exam like Question 1

Exam like Question 2

Exam like Question 3

Total Probability Rule

Ücretsiz

Bayes Rule

Exam like Question 1

Exam like Question 2

Exam like Question 3

Introduction to Independence

Independence 2

Independence 3

Exam like Question 1

Exam like Question 2

Exam like Question 3

Exam like Question 4

Axioms of Probability 1

Ücretsiz

Axioms of Probability 2

Ücretsiz

Axioms of Probability 3

Conditional Probability 1

Conditional Probability 2

Conditional Probability 3

Independence 1

Ücretsiz

Independence 2

Ücretsiz

Independence 3

Bayes' Rule 1

Bayes' Rule 2

Ücretsiz

Bayes' Rule 3

Ücretsiz

Bayes' Rule 4

Bayes' Rule 5

Probability Mass Functions

Ücretsiz

Expected Value

PMF Tables

Exam Like Question 1

Exam Like Question 2

Deriving New Variables From Old Ones

Variance

Exam Like Question 3

Ücretsiz

Exam Like Question 4

Ücretsiz

Expected Value and Variance Arithmetic

Cumulative Distribution Function

Exam Like Question 5

What is continuous anyway?

Ücretsiz

Example 1

Example 2

Example 3

Example 4

Exam Like Question 1

Ücretsiz

Expected Value and Variance

Example 5

Example 6

Cumulative Distribution Function (CDF)

Finding f(x) Given F(x)

Example 7

Exam Like Question 2

Discrete Random Variables 1

Ücretsiz

Discrete Random Variables 2

Discrete Random Variables 3

Ücretsiz

Discrete Random Variables 4

Discrete Random Variables 5

Discrete Random Variables 6

Ücretsiz

Discrete Random Variables 7

Discrete Random Variables 8

Continuous Random Variables 1

Ücretsiz

Continuous Random Variables 2

Continuous Random Variables 3

Continuous Random Variables 4

Ücretsiz

Continuous Random Variables 5

Ücretsiz

Continuous Random Variables 6

Bernoulli Distribution Part 1

Bernoulli Distribution Part 2

Example 1

Example 2

Binomial Distribution Part 1

Binomial Distribution Part 2

Example 3

Example 4

Poisson Distribution Part 1

Poisson Distribution Part 2

Example 5

Example 6

Poisson Approximation to Binomial Distribution

Example 7

Hypergeometric Distribution

Example 8

Geometric Distribution Part 1

Geometric Distribution Part 2

Example 9

Example 10

Negative Binomial Distribution Part 1

Negative Binomial Distribution Part 2

Example 11

Example 12

Uniform Distribution

Example 1

Exam Like Question 1

Exam Like Question 2

Exponential Distribution

Example 2

Ücretsiz

Example 3

Memoryless Property

Exam Like Question 3

Ücretsiz

Exam Like Question 4

Normal Distribution

Standard Normal Distribution

Exam Like Question 5

Exam Like Question 6

Normal Approximation to Binomial Distribution

Example 4

Poisson Distribution 1

Poisson Distribution 2

Ücretsiz

Poisson Distribution 3

Ücretsiz

Binomial Distribution 1

Binomial Distribution 2

Ücretsiz

Binomial Distribution 3

Binomial Distribution 4

Poisson Approximation to Binomial 1

Ücretsiz

Poisson Approximation to Binomial

Geometric Distribution 1

Ücretsiz

Geometric Distribution 2

Geometric Distribution 3

Uniform Distribution 1

Ücretsiz

Uniform Distribution 2

Uniform Distribution 3

Exponential Distribution 1

Exponential Distribution 2

Ücretsiz

Exponential Distribution 3

Exponential Distribution 4

Exponential Distribution 5

Ücretsiz

Normal Distribution 1

Normal Distribution 2

Normal Distribution 3

Ücretsiz

Normal Distribution 4

Ücretsiz

Normal Distribution 5

Joint and Marginal PMF

Examples

Conditional PMF

Ücretsiz

Exam Like Question 1

Ücretsiz

Exam Like Question 2

Exam Like Question 3

Ücretsiz

Joint and Marginal PDF

Example 1

Exam Like Question 1

Ücretsiz

Exam Like Question 2

Ücretsiz

Conditional PDF

Example 2

Exam Like Question 3

Exam Like Question 4

Covariance

Example 1 (Discrete)

Example 2 (Continuous)

Example 3 (Continuous)

Variance of Sums

Example 4

Correlation

Example 5

Discrete Joint Distribution 1

Discrete Joint Distribution 2

Discrete Joint Distribution 3

Ücretsiz

Continous Joint Distribution 1

Continuous Joint Distribution 2

Continuous Joint Distribution 3

Ücretsiz

Continuous Joint Distribution 4

Continuous Joint Distribution 5

Joint Statistics 1

Ücretsiz

Joint Statistics 2

Ücretsiz

Joint Statistics 3

Joint Statistics 4

Ücretsiz

Question 1

Ücretsiz

Question 2

Ücretsiz

Question 3

Question 4

Question 5

Question 6

## Eğitmenler

Ömer Faruk Altun
MSCS

2011 yılında Endüstri Mühendisliği okumak için başladığım Sabancı Üniversitesi'nden 2018 yılında Bilgisayar Mühendisi olarak mezun oldum. Şu anda UALR'da Information Science doktora eğitimimi sürdürüyorum. 7 yıldır Altun ismiyle başta Sabancı Üniversitesi olmak üzere çeşitli okullarda Endüstri ve Bilgisayar Mühendisliği alanlarında ders vermekteyim.

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.

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