MATH 217 • Tüm Sınavlar • Probability and Statistics
Bu ders ile MATH 217 sınavı için temel konseptleri çok iyi anlamakla kalmayıp sınava girmeye de tamamen hazır olacaksın.
Dersin içeriğinde yer alan Permutation, Combination, Binomial Theorem, Rules 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.
Ayda 1599 TL, peşin fiyatına 3 taksit
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.
Konular
Axioms of Probability
11 konu anlatımı
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, Bayes' Rule and Independence
14 konu anlatımı
Conditioning Events
Total Probability Rule
Example 1
Example 2
Example 3
Example 4
Example 5
Example 6
Bayes' Rule
Bayes' Rule Example 1
Bayes' Rule Example 2
Independence
Independence Example 1
Independence Example 2
Sample Midterm Problems I
20 soru
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
Bayes' Rule 1
Bayes' Rule 2
Bayes' Rule 3
Bayes' Rule 4
Bayes' Rule 5
Bayes' Rule 6
Bayes' Rule 7
Bayes' Rule 8
Bayes' Rule 9
Discrete Random Variables
12 konu anlatımı
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
Sample Midterm Problems II
11 soru
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
Discrete Random Variables 9
Discrete Random Variables 10
Discrete Random Variables 11
Special Discrete Distributions
24 konu anlatımı
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
Sample Midterm Problems III
18 soru
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
Hypergeometric Distribution 4
Discrete Uniform Distribution
Negative Binomial Distribution 1
Negative Binomial - Geometric Distribution
Geometric Distribution 1
Geometric Distribution 2
Geometric Distribution 3
Continuous Random Variables
9 konu anlatımı
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 Continuous Distributions
17 konu anlatımı
Uniform Distribution
Example 1
Example 2
Exponential Distribution
Example 3
Example 4
Memoryless Property
Example 5
Normal Distribution
Standard Normal Distribution
Reading Z Table - Option 1
Reading Z Table - Option 2
Example 6
Gamma Distribution
Example 7
Relation of Gamma Distribution with Others
Weibull Distribution
Sample Midterm Problems I
20 soru
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
Uniform Distribution 3
Exponential Distribution 1
Exponential Distribution 2
Exponential Distribution 3
Exponential Distribution 4
Normal Distribution 1
Normal Distribution 2
Normal Distribution 3
Normal Distribution 4
Normal Distribution 5
Normal Distribution 6
Normal Distribution 7
Multiple Random Variable (Discrete)
10 konu anlatımı
Probability Mass Function
PMF Example
Marginal PMF and CDF
Expected Value
Variance
Expected Value and Variance Example
Conditional PMF and CDF
Conditional Expectation
End of Topic Example - Part I
End of Topic Example - Part II
Multiple Random Variable (Continuous)
8 konu anlatımı
Introduction
Marginal PDF and CDF
Expected Value and Variance
Conditional PDF and CDF
Conditional Expectation
Example 1
Example 2
Example 3
Sample Midterm Problems II
16 soru
Discrete Joint Probability 1
Discrete Joint Probability 2
Discrete Joint Probability 3
Discrete Joint Probability 4
Discrete Joint Probability 5
Continuous Joint Probability 1
Continuous Joint Probability 2
Continuous Joint Probability 3
Continuous Joint Probability 4
Continuous Joint Probability 5
Continuous Joint Probability 6
Continuous Joint Probability 7
Continuous Joint Probability 8
Continuous Joint Probability 9
Continuous Joint Probability 10
Continuous Joint Probability 11
Joint Statistics
8 konu anlatımı · 4 soru
Covariance
Example 1 (Discrete)
Example 2 (Continuous)
Example 3 (Continuous)
Exam Like Question 1
Exam Like Question 2
Variance of Sums
Example 4
Correlation
Example 5
Exam Like Question 3
Exam Like Question 4
Sample Midterm Problems III
10 soru
Joint Statistics 1
Joint Statistics 2
Joint Statistics 3
Joint Statistics 4
Joint Statistics 5
Joint Statistics 6
Joint Statistics 7
Joint Statistics 8
Joint Statistics 9
Joint Statistics 10
Functions of Random Variables
3 konu anlatımı
Distribution Function Techniques
Example 1
Example 2
Samples and Distribution of the Mean
11 konu anlatımı
Sample Mean
Sample Variance
Example 1
Central Limit Theorem
Example 1
Example 2
Example 3
Example 4
Example 5
Normal Approximation to Binomial Distribution
Normal Approximation to Poisson Distribution
Sampling Distributions
5 konu anlatımı · 2 soru
Z Distribution
Example 1
Exam Like Question 1
T Distribution
Example 3
Example 4
Exam Like Question 2
Sample Final Problems II
19 soru
Distribution Function Technique 1
Distribution Function Technique 2
Distribution Function Technique 3
Z Distribution 1
Z Distribution 2
Z Distribution 3
Z Distribution 4
Z Distribution 5
Z Distribution 6
Z Distribution 7
Z Distribution 8
Z Distribution 9
Z Distribution 10
Normal Approximation to Binomial Distribution 1
Normal Approximation to Binomial Distribution 2
Normal Approximation to Binomial Distribution 3
T Distribution 1
T Distribution 2
T Distribution 3
Confidence Interval for Means
7 konu anlatımı · 1 soru
Confidence Interval for Means(Sigma known)
Example 1
Example 2
Example 3
Exam Like Question 1
Confidence Interval for Means (sigma unknown)
Example 4
Example 5
Hypothesis Testing for Means
6 konu anlatımı · 2 soru
Introduction
Tests for Mean
Example 1
Example 2
Example 3
Example 4
Exam like Question 1
Exam like Question 2
Sample Final Problems III
17 soru
C.I. of Mean (Known Variance) 1
C.I. of Mean (Known Variance) 2
C.I. of Mean (Known Variance) 3
C.I. of Mean (Unknown Variance) 1
C.I. of Mean (Unknown Variance) 2
C.I. of Mean (Unknown Variance) 3
Testing for the Mean 1
Testing for the Mean 2
Testing for the Mean 3
Testing for the Mean 4
Testing for the Mean 5
Testing for the Mean 6
Testing for the Mean 7
Testing for the Mean 8
Testing for the Mean 9
Testing for the Mean 10
Testing for the Mean 11