CE 202 • Final • Introduction to Probability and Statistics
Her mühendisliğin temelinde var olan Olasılık ve İstatistik konularının uygulamalarını gördüğümüz bu derste: 1) Mathematical Expectation 2) Discrete Probability Distributions 3) Continuous Probability Distributions konularını inceliyoruz.
Sınava yönelik sorular ile konuların en kritik soru tiplerini kolaydan zora çözüp sınavda sürprize yer bırakmıyoruz!
Dersi 3 kişi birlikte alın
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.
Memnuniyet Garantisi
Bu dersi alma kararını senin için kolaylaştıralım. Eğer memnun kalmazsan 30 gün içinde bize ulaş, 3'ten fazla içerik tamamlamadıysan iade alabilirsin.
Tüm koşullarPaketi Tamamla
🎓 Başkent Üniversitesinde öğrencilerin %92'si tüm paketi alarak çalışıyor.
CE 202 • Midterm
Introduction to Probability and Statistics
İhsan Altundağ
1499 TL
CE 202 • Final
Introduction to Probability and Statistics
İhsan Altundağ
1499 TL
Konular
Mathematical Expected Value, Variance and Covariance
Expected Value for Discrete RV
Example 1
Example 2
Variance for Discrete RV
Example 3
Example 4
Expected Value for Continuous RV
Example 5
Example 6
Variance for Continuous RV
Example 7
Expected Value for Discrete Joint RV
Variance for Discrete Joint RV
Example 8
Conditional Expectation for Discrete Joint RV
Example 9
Example 10
Expected Value and Variance for Continuous Joint RV
Conditional Expectation for Continuous Joint RV
Example 11
Covariance
Correlation
Some Discrete Probability Distributions
Discrete Uniform Distribution Part 1
Discrete Uniform Distribution Part 2
Bernoulli Distribution Part 1
Bernoulli Distribution Part 2
Binomial Distribution Part 1
Binomial Distribution Part 2
Poisson Distribution Part 1
Poisson Distribution Part 2
Poisson Approximation to Binomial Distribution
Geometric Distribution Part 1
Geometric Distribution Part 2
Hypergeometric Distribution
Negative Binomial Distribution Part 1
Negative Binomial Distribution Part 2
Some Continuous Probability Distributions
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
Reading Tables
T Table
Chi Square Table
F Table
Sampling Distribution of Sample Mean and Sample Variance
Sample Mean
Sample Variance
Central Limit Theorem
Z Distribution
Chi Square Distribution
T Distribution
F Distribution
One and Two Sample Estimation
Point Estimation
Unbiased Estimators
Example 1
Efficient Estimators
Interval Estimation
Table Values
Estimating Mean when Sigma is Known
Estimating Mean when Sigma is Unknown
Prediction Interval for Means
Tolerance Intervals for Means
Estimating Difference Between Means when Sigma is Known
Estimating Difference Between Means when Sigma is Unknown
Estimating a Proportion
Estimating Difference Between Proportions
Estimating the Variance
Estimating the Ratio of Two Variances
Regression and Correlation
Regression Equations
Least Squares and the Fitted Model
Example 1
Example 2
Coefficient of Determination
Properties of Least Squares Estimators
Example 3
Partition of Total Variability and Estimation of Sigma
Slope Paremeter
Test for Slope Parameter
Confidence Interval for Slope Parameter
Example 2
Sample Exam Problems
Mathematical Expectation 1 - Discrete R.V.
Mathematical Expectation 2 - Discrete R.V.
Mathematical Expectation 3 - Discrete R.V
Mathematical Expectation 4 - Discrete R.V.
Mathematical Expectation 5 - Discrete R.V.
Mathematical Expectation 6 - Continuous R.V.
Mathematical Expectation 7 - Continuous R.V.
Mathematical Expectation 8 - Discrete Joint
Mathematical Expectation 9 - Continuous Joint
Mathematical Expectation 10 - Continuous Joint
Mathematical Expectation 11 - Covariance
Mathematical Expectation 12 - Covariance
Mathematical Expectation 13 - Covariance
Binomial Distribution 1
Binomial Distribution 2
Binomial Distribution 3
Poisson distribution 1
Poisson distribution 2
Poisson Distribution 3
Hypergeometric Distribution 1
Hypergeometric Distribution 2
Negative Binomial Distribution
Negative Binomial - Geometric Distribution
Geometric Distribution 1
Geometric Distribution 2
Uniform Distribution - Continuous
Exponential Distribution 1
Exponential Distribution 2
Normal Distribution 1
Normal Distribution 2
Normal Distribution 3
Normal Distribution 4
Normal Distribution 5
Normal Distribution 6
Central Limit Theorem 1
Central Limit Theorem 2
Central Limit Theorem 3
Central Limit Theorem 4
Central Limit Theorem 5
Central Limit Theorem 6
Fundamental Sampling Distributions 1
Fundamental Sampling Distributions 2
Fundamental Sampling Distributions 3
Fundamental Sampling Distributions 4
Fundamental Sampling Distributions 5
One-Sample Estimation Problems 1
One-Sample Estimation Problems 2
One-Sample Estimation Problems 3
One-Sample Estimation Problems 4
One-Sample Estimation Problems 5
One-Sample Estimation Problems 6
One-Sample Estimation Problems 7
One-Sample Estimation Problems 8
One-Sample Estimation Problems 9
One-Sample Estimation Problems 10
Two-Samples Estimation Problems 1
Two-Samples Estimation Problems 2
Two-Samples Estimation Problems 3
Two-Samples Estimation Problems 4
Simple Linear Regression 1
Simple Linear Regression 2
Değerlendirmeler
Henüz hiç değerlendirme yok.
Ders İçeriği
Mathematical Expected Value, Variance and Covariance
Expected Value for Discrete RV
Example 1
Example 2
Variance for Discrete RV
Example 3
Example 4
Expected Value for Continuous RV
Example 5
Example 6
Variance for Continuous RV
Example 7
Expected Value for Discrete Joint RV
Variance for Discrete Joint RV
Example 8
Conditional Expectation for Discrete Joint RV
Example 9
Example 10
Expected Value and Variance for Continuous Joint RV
Conditional Expectation for Continuous Joint RV
Example 11
Covariance
Correlation
Some Discrete Probability Distributions
Discrete Uniform Distribution Part 1
Discrete Uniform Distribution Part 2
Bernoulli Distribution Part 1
Bernoulli Distribution Part 2
Binomial Distribution Part 1
Binomial Distribution Part 2
Poisson Distribution Part 1
Poisson Distribution Part 2
Poisson Approximation to Binomial Distribution
Geometric Distribution Part 1
Geometric Distribution Part 2
Hypergeometric Distribution
Negative Binomial Distribution Part 1
Negative Binomial Distribution Part 2
Some Continuous Probability Distributions
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
Reading Tables
T Table
Chi Square Table
F Table
Sampling Distribution of Sample Mean and Sample Variance
Sample Mean
Sample Variance
Central Limit Theorem
Z Distribution
Chi Square Distribution
T Distribution
F Distribution
One and Two Sample Estimation
Point Estimation
Unbiased Estimators
Example 1
Efficient Estimators
Interval Estimation
Table Values
Estimating Mean when Sigma is Known
Estimating Mean when Sigma is Unknown
Prediction Interval for Means
Tolerance Intervals for Means
Estimating Difference Between Means when Sigma is Known
Estimating Difference Between Means when Sigma is Unknown
Estimating a Proportion
Estimating Difference Between Proportions
Estimating the Variance
Estimating the Ratio of Two Variances
Regression and Correlation
Regression Equations
Least Squares and the Fitted Model
Example 1
Example 2
Coefficient of Determination
Properties of Least Squares Estimators
Example 3
Partition of Total Variability and Estimation of Sigma
Slope Paremeter
Test for Slope Parameter
Confidence Interval for Slope Parameter
Example 2
Sample Exam Problems
Mathematical Expectation 1 - Discrete R.V.
Mathematical Expectation 2 - Discrete R.V.
Mathematical Expectation 3 - Discrete R.V
Mathematical Expectation 4 - Discrete R.V.
Mathematical Expectation 5 - Discrete R.V.
Mathematical Expectation 6 - Continuous R.V.
Mathematical Expectation 7 - Continuous R.V.
Mathematical Expectation 8 - Discrete Joint
Mathematical Expectation 9 - Continuous Joint
Mathematical Expectation 10 - Continuous Joint
Mathematical Expectation 11 - Covariance
Mathematical Expectation 12 - Covariance
Mathematical Expectation 13 - Covariance
Binomial Distribution 1
Binomial Distribution 2
Binomial Distribution 3
Poisson distribution 1
Poisson distribution 2
Poisson Distribution 3
Hypergeometric Distribution 1
Hypergeometric Distribution 2
Negative Binomial Distribution
Negative Binomial - Geometric Distribution
Geometric Distribution 1
Geometric Distribution 2
Uniform Distribution - Continuous
Exponential Distribution 1
Exponential Distribution 2
Normal Distribution 1
Normal Distribution 2
Normal Distribution 3
Normal Distribution 4
Normal Distribution 5
Normal Distribution 6
Central Limit Theorem 1
Central Limit Theorem 2
Central Limit Theorem 3
Central Limit Theorem 4
Central Limit Theorem 5
Central Limit Theorem 6
Fundamental Sampling Distributions 1
Fundamental Sampling Distributions 2
Fundamental Sampling Distributions 3
Fundamental Sampling Distributions 4
Fundamental Sampling Distributions 5
One-Sample Estimation Problems 1
One-Sample Estimation Problems 2
One-Sample Estimation Problems 3
One-Sample Estimation Problems 4
One-Sample Estimation Problems 5
One-Sample Estimation Problems 6
One-Sample Estimation Problems 7
One-Sample Estimation Problems 8
One-Sample Estimation Problems 9
One-Sample Estimation Problems 10
Two-Samples Estimation Problems 1
Two-Samples Estimation Problems 2
Two-Samples Estimation Problems 3
Two-Samples Estimation Problems 4
Simple Linear Regression 1
Simple Linear Regression 2
Memnuniyet Garantisi
Bu dersi alma kararını senin için kolaylaştıralım. Eğer memnun kalmazsan 30 gün içinde bize ulaş, 3'ten fazla içerik tamamlamadıysan iade alabilirsin.
Tüm koşullarSıkça 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.