ENGR 240 • Midterm • Probability and Statistics for Engineers and Scientists
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
Axioms of Probability
Axioms of Probability 1
Axioms of Probability 2
Axioms of Probability 3
Axioms of Probability 4
Conditional Probability
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 & Bayes' Theorem
Total Probability Rule
Bayes Rule
Exam like Question 1
Exam like Question 2
Exam like Question 3
Independence
Introduction to Independence
Independence 2
Independence 3
Exam like Question 1
Exam like Question 2
Exam like Question 3
Exam like Question 4
Sample Midterm Part I
Axioms of Probability 1
Axioms of Probability 2
Axioms of Probability 3
Conditional Probability 1
Conditional Probability 2
Conditional Probability 3
Independence 1
Independence 2
Independence 3
Bayes' Rule 1
Bayes' Rule 2
Bayes' Rule 3
Bayes' Rule 4
Bayes' Rule 5
Discrete Random Variables
Probability Mass Functions
Expected Value
PMF Tables
Exam Like Question 1
Exam Like Question 2
Deriving New Variables From Old Ones
Variance
Exam Like Question 3
Exam Like Question 4
Expected Value and Variance Arithmetic
Cumulative Distribution Function
Exam Like Question 5
Continuous Random Variables
What is continuous anyway?
Example 1
Example 2
Example 3
Example 4
Exam Like Question 1
Expected Value and Variance
Example 5
Example 6
Cumulative Distribution Function (CDF)
Finding f(x) Given F(x)
Example 7
Exam Like Question 2
Sample Midterm Part 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 Variables 7
Discrete Random Variables 8
Continuous Random Variables 1
Continuous Random Variables 2
Continuous Random Variables 3
Continuous Random Variables 4
Continuous Random Variables 5
Continuous Random Variables 6
Special Discrete Distributions
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
Special Continuous Distributions
Uniform Distribution
Example 1
Exam Like Question 1
Exam Like Question 2
Exponential Distribution
Example 2
Example 3
Memoryless Property
Exam Like Question 3
Exam Like Question 4
Normal Distribution
Standard Normal Distribution
Reading Z Table (Option 1)
Reading Z Table (Option 2)
Reading Z Table
Exam Like Question 5
Exam Like Question 6
Normal Approximation to Binomial Distribution
Example 4
Sample Midterm Part III
Poisson Distribution 1
Poisson Distribution 2
Poisson Distribution 3
Binomial Distribution 1
Binomial Distribution 2
Binomial Distribution 3
Binomial Distribution 4
Poisson Approximation to Binomial 1
Poisson Approximation to Binomial
Geometric Distribution 1
Geometric Distribution 2
Geometric Distribution 3
Uniform Distribution 1
Uniform Distribution 2
Uniform Distribution 3
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
Discrete Joint Distribution
Joint and Marginal PMF
Examples
Conditional PMF
Exam Like Question 1
Exam Like Question 2
Exam Like Question 3
Continous Joint Distribution
Joint and Marginal PDF
Example 1
Exam Like Question 1
Exam Like Question 2
Conditional PDF
Example 2
Exam Like Question 3
Exam Like Question 4
Joint Statistics
Covariance
Example 1 (Discrete)
Example 2 (Continuous)
Example 3 (Continuous)
Variance of Sums
Example 4
Correlation
Example 5
Sample Midterm Part IV
Discrete Joint Distribution 1
Discrete Joint Distribution 2
Discrete Joint Distribution 3
Continous Joint Distribution 1
Continuous Joint Distribution 2
Continuous Joint Distribution 3
Continuous Joint Distribution 4
Continuous Joint Distribution 5
Joint Statistics 1
Joint Statistics 2
Joint Statistics 3
Joint Statistics 4
Sample Midterm
Question 1
Question 2
Question 3
Question 4
Question 5
Question 6
Eğitmenler
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. 11 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.
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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