Bu ders ile MATH 211 sınavı için temel konseptleri çok iyi anlamakla kalmayıp sınava girmeye de tamamen hazır olacaksın.
Dersin içeriğinde yer alan , Joint Probability Distribution, Marginal Distribution, Covariance, Independence, Conditional Expectation & Variance ve Estimation kavramlarını çok iyi öğreneceksin ve hepsine dair en az birer örnek soru göreceksin.
Discrete Joint Probability
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
Continuous Joint Probability
Introduction
Marginal PDF and CDF
Expected Value and Variance
Conditional PDF and CDF
Conditional Expectation
Example 1
Example 2
Example 3
Joint Statistics
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 Part I
Discrete Joint Distribution 1
Discrete Joint Distribution 2
Discrete Joint Distribution 3
Discrete Joint Distribution 4
Discrete Joint Distribution 5
Continuous Joint Probability 1
Continuous Joint Probability 2
Continuous Joint Distribution 3
Continuous Joint Distribution 4
Continuous Joint Distribution 5
Continuous Joint Distribution 6
Joint Statistics 1
Joint Statistics 2
Joint Statistics 3
Joint Statistics 4
Joint Statistics 5
Point Estimation : Part 1
Introduction
Unbiased Estimators 1
Unbiased Estimators 2
Exam like Question 1
Exam like Question 2
Exam like Question 3
Efficient Estimators
Exam like Question 4
Exam Like Question 5
Consistent Estimators 1
Consistent Estimators 2
Consistent Estimators 3
Exam like Question 6
Sufficient Estimators 1
Sufficient Estimators 2
Exam Like Question 7
Chapter Summary
Point Estimation: Part 2
Method of Moments
Example 1
Example 2
Example 3
Example 4
Method of Maximum Likelihood
Example 5
Example 6
Example 7
Example 8
Chapter Summary
Sample Midterm Part II
Unbiased Estimators 1
Unbiased Estimators 2
Unbiased Estimators 3
Consistent Estimator
Unbiased and Consistent Estimator 1
Unbiased and Consistent Estimator 2
Efficient Estimators 1
Efficient Estimators 2
Sufficient Estimator
Maximum Likelihood Estimators 1
Maximum Likelihood Estimators 2
Method of Moments and Maximum Likelihood
Reading Tables
Reading Z Table - Option 1
Reading Z Table - Option 2
Reading T Table
Reading Chi Table
Reading F Table
Sampling Distributions: Part 1
Sample Mean
Sample Variance
Example 1
Central Limit Theorem
Example 2
Example 3
Example 4
Example 5
Example 6
Sampling Distributions: Part 2
Z Distribution
Example 1
Exam Like Question 1
Chi Square Distribution
Example 2
T Distribution
Example 3
Example 4
Exam Like Question 2
F Distribution
Example 5
Example 6
Exam Like Question 3
Chapter Summary
Sample Midterm Part III
Z Distribution 1
Z Distribution 2
Z Distribution 3
Z Distribution 4
Z Distribution 5
Z Distribution 6
Z Distribution 7
T Distribution 1
T Distribution 2
T Distribution 3
Chi Square Distribution 1
Chi Square Distribution 2
Chi Square Distribution 3
Chi Square Distribution 4
F Distribution 1
F Distribution 2
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.
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.
1299 TL