IE 201 • Midterm II • Probability and Statistics I
Olasılıkla başlayıp, İstatistikle biten bu dersimizde özet ve uygulamaları konu anlatımlarıyla temelleri atıyor; sayısız çözümlü soru örneğiyle sınavlara hazır hale geliyoruz!
Eğitmen
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.
Paketi Tamamla
🎓 Atılım Üniversitesinde öğrencilerin %92'si tüm paketi alarak çalışıyor.
Konular
Mathematical Expectation and Variances: Discrete
Expected Value
Expected Value Example 1
Expected Value Example 2
Variance
Variance Example 1
Variance Example 2
End of Topic Questions
Discrete Random Variables 1 - Expected Value
Discrete Random Variables 2 - Expected Value
Discrete Random Variables 3 - Variance
Discrete Random Variables 4 - Expected Value
Discrete Random Variables 5 - Expected Value and Variance
Discrete Random Variables 6 - Expected Value
Mathematical Expectation and Variances: Continous
Expected Value
Expected Value - Example 1
Expected Value - Example 2
Variance
Variance - Example 1
End of Topic Questions
Continuous Random Variable 1 - Expected Value
Continuous Random Variable 2 - Expected Value
Continuous Random Variable 3 - Variance
Continous Random Variable 4 - Expected Value
Continuous Random Variables 5 - Expected Value and Variance
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
End of Topic Questions
Discrete Joint Probability 1
Discrete Joint Probability 2
Discrete Joint Probability 3 - Expected Value
Discrete Joint Probability 4 - Expected Value
Continuous Joint Probability
Introduction
Marginal PDF and CDF
Expected Value and Variance
Conditional PDF and CDF
Conditional Expectation
Example 1
Example 2
Example 3
End of Topic Questions
Continuous Joint Probability 1
Continuous Joint Probability 2
Continuous Joint Probability 3
Continuous Joint Probability 4
Continuous Joint Probability 5 - Expected Value
Covariance and Correlation
Covariance
Example 1
Example 2
Example 3
Variance of Sums
Example 4
Correlation
Example 5
End of Topic Questions
Covariance 1
Covariance 2
Correlation
Some Discrete Probability Distributions: Part 1
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
End of Topic Questions
Binomial Distribution 1
Binomial Distribution 2
Binomial Distribution 3
Multinomial Distribution 1
Multinomial Distribution 2
Poisson distribution 1
Poisson Distribution 2
Poisson Distribution 3
Poisson distribution 4
Hypergeometric Distribution 1
Hypergeometric Distribution 2
Hypergeometric Distribution 3
Hypergeometric Distribution 4
Hypergeometric Distribution 5
Değerlendirmeler
Henüz hiç değerlendirme yok.
Ders İçeriği
Mathematical Expectation and Variances: Discrete
Expected Value
Expected Value Example 1
Expected Value Example 2
Variance
Variance Example 1
Variance Example 2
End of Topic Questions
Discrete Random Variables 1 - Expected Value
Discrete Random Variables 2 - Expected Value
Discrete Random Variables 3 - Variance
Discrete Random Variables 4 - Expected Value
Discrete Random Variables 5 - Expected Value and Variance
Discrete Random Variables 6 - Expected Value
Mathematical Expectation and Variances: Continous
Expected Value
Expected Value - Example 1
Expected Value - Example 2
Variance
Variance - Example 1
End of Topic Questions
Continuous Random Variable 1 - Expected Value
Continuous Random Variable 2 - Expected Value
Continuous Random Variable 3 - Variance
Continous Random Variable 4 - Expected Value
Continuous Random Variables 5 - Expected Value and Variance
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
End of Topic Questions
Discrete Joint Probability 1
Discrete Joint Probability 2
Discrete Joint Probability 3 - Expected Value
Discrete Joint Probability 4 - Expected Value
Continuous Joint Probability
Introduction
Marginal PDF and CDF
Expected Value and Variance
Conditional PDF and CDF
Conditional Expectation
Example 1
Example 2
Example 3
End of Topic Questions
Continuous Joint Probability 1
Continuous Joint Probability 2
Continuous Joint Probability 3
Continuous Joint Probability 4
Continuous Joint Probability 5 - Expected Value
Covariance and Correlation
Covariance
Example 1
Example 2
Example 3
Variance of Sums
Example 4
Correlation
Example 5
End of Topic Questions
Covariance 1
Covariance 2
Correlation
Some Discrete Probability Distributions: Part 1
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
End of Topic Questions
Binomial Distribution 1
Binomial Distribution 2
Binomial Distribution 3
Multinomial Distribution 1
Multinomial Distribution 2
Poisson distribution 1
Poisson Distribution 2
Poisson Distribution 3
Poisson distribution 4
Hypergeometric Distribution 1
Hypergeometric Distribution 2
Hypergeometric Distribution 3
Hypergeometric Distribution 4
Hypergeometric Distribution 5
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.