MATH 2205 • Midterm • Applied Probability and Statistics for Engineers
Her mühendisliğin temelinde var olan Olasılık ve İstatistik konularının uygulamalarını gördüğümüz bu derste sınava yönelik sorular ile konuların en kritik soru tiplerini kolaydan zora çözüp sınavda sürprize yer bırakmıyoruz!
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
🎓 Işık Üniversitesinde öğrencilerin %92'si tüm paketi alarak çalışıyor.
Konular
Introduction to Statistics
Introduction
Frequency Distribution
Example 1
Relative Frequency Distribution
Example 2
Cumulative Frequency Distribution
Example 3
Frequency Histogram
Measures of Central Tendancy
Example 4
Measures of Dispersion
Example 5
Example 6
Example 7
Skewness and Kurtosis
Stem and Leaf Diagram
Example 8
Example 9
Box and Whisker Plot
Example 10
Comparing Boxplots
Example 11
Example 12
Axioms of Probability
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
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
Introduction to Statistics 1
Introduction to Statistics 2
Introduction to Statistics 3
Introduction to Statistics 4
Introduction to Statistics 5
Introduction to Statistics 6
Introduction to Statistics 7
Axioms of Probability 1
Axioms of Probability 2
Axioms of Probability 3
Axioms of Probability 4
Conditional Probability and Independence 1
Conditional Probability and Independence 2
Conditional Probability and Independence 3
Conditional Probability and Independence 4
Conditional Probability and Independence 5
Conditional Probability and Independence 6
Conditional Probability and Independence 7
Conditional Probability and Independence 8
Conditional Probability and Independence 9
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
Random Variables
Probability Mass Function (PMF) for Discrete RV
PMF Example 1
PMF Example 2
Cumulative Distribution Function for Discrete RV
CDF Example
Continuous Random Variables
Probability Density Function (PDF) for Continuous RV
PDF Example
Cumulative Distribution Function (CDF) for Continuous RV
CDF Example
Sample Midterm Problems II
Discrete Random Variable 1
Discrete Random Variable 2
Discrete Random Variable 3
Discrete Random Variable 4
Discrete Random Variable 5
Discrete Random Variable 6
Discrete Random Variable 7
Continuous Random Variable 1
Continuous Random Variable 2
Continuous Random Variable 3
Continuous Random Variable 4
Continuous Random Variable 5
Continuous Random Variable 6
Continuous Random Variable 7
Joint Probability Distributions
Discrete Joint Random Variables
Discrete Joint RV Example
Marginal PMF and CDF for Discrete Joint RV
Conditional PMF and CDF for Discrete Joint RV
Continuous Joint Random Variables
Marginal PDF and CDF for Continuous Joint RV
Conditional PDF and CDF for Continuous Joint RV
Mathematical Expectation & Variance
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
Expected Value and Variance for Continuous Joint RV
Covariance and Correlation Coefficient
Covariance
Example 1
Example 2
Example 3
Variance of Sums
Example 4
Correlation Coefficient
Example 5
Sample Midterm Problems III
Discrete Random Variable 1- Expected Value
Discrete Random Variable 2 - Expected Value
Discrete Random Variable 3 - Variance
Discrete Random Variable 4- Expected Value
Discrete Random Variable 5 - Expected Value
Discrete Random Variable 6 - Expected Value and Variance
Continuous Random Variable 1 - Expected Value
Continuous Random Variable 2 - Expected Value
Continuous Random Variable 3 - Variance
Continuous Random Variable 4 - Expected Value
Continuous Random Variable 5 - Expected Value and Variance
Discrete Joint Distribution 1
Discrete Joint Distribution 2
Discrete Joint Distribution 3
Continuous Joint Distribution 1
Continuous Joint Distribution 2
Continuous Joint Distribution 3
Continuous Joint Distribution 4
Covariance 1
Covariance 2
Covariance 3
Correlation Coefficient
Some Discrete Probability Distributions
Chebyshev's Inequality
Example
Bernoulli Distribution Part 1
Bernoulli Distribution Part 2
Example 1
Example 2
Binomial Distribution Part 1
Binomial Distribution Part 2
Example 3
Example 4
Hypergeometric Distribution
Example 5
Some Continuous Probability Distributions
Uniform Distribution
Example 1
Example 2
Normal Distribution
Standard Normal Distribution
Reading Z Table - Option 1
Reading Z Table - Option 2
Example 3
Sample Midterm Problems IV
Chebyshev's Theorem
Binomial Distribution 1
Binomial Distribution 2
Binomial Distribution 3
Binomial Distribution 4
Hypergeometric Distribution 1
Hypergeometric Distribution 2
Hypergeometric Distribution 3
Hypergeometric Distribution 4
Uniform Distribution 1
Uniform Distribution 2
Uniform Distribution 3
Normal Distribution 1
Normal Distribution 2
Normal Distribution 3
Normal Distribution 4
Normal Distribution 5
Normal Distribution 6
Normal Distribution 7
Değerlendirmeler
Henüz hiç değerlendirme yok.
Ders İçeriği
Introduction to Statistics
Introduction
Frequency Distribution
Example 1
Relative Frequency Distribution
Example 2
Cumulative Frequency Distribution
Example 3
Frequency Histogram
Measures of Central Tendancy
Example 4
Measures of Dispersion
Example 5
Example 6
Example 7
Skewness and Kurtosis
Stem and Leaf Diagram
Example 8
Example 9
Box and Whisker Plot
Example 10
Comparing Boxplots
Example 11
Example 12
Axioms of Probability
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
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
Introduction to Statistics 1
Introduction to Statistics 2
Introduction to Statistics 3
Introduction to Statistics 4
Introduction to Statistics 5
Introduction to Statistics 6
Introduction to Statistics 7
Axioms of Probability 1
Axioms of Probability 2
Axioms of Probability 3
Axioms of Probability 4
Conditional Probability and Independence 1
Conditional Probability and Independence 2
Conditional Probability and Independence 3
Conditional Probability and Independence 4
Conditional Probability and Independence 5
Conditional Probability and Independence 6
Conditional Probability and Independence 7
Conditional Probability and Independence 8
Conditional Probability and Independence 9
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
Random Variables
Probability Mass Function (PMF) for Discrete RV
PMF Example 1
PMF Example 2
Cumulative Distribution Function for Discrete RV
CDF Example
Continuous Random Variables
Probability Density Function (PDF) for Continuous RV
PDF Example
Cumulative Distribution Function (CDF) for Continuous RV
CDF Example
Sample Midterm Problems II
Discrete Random Variable 1
Discrete Random Variable 2
Discrete Random Variable 3
Discrete Random Variable 4
Discrete Random Variable 5
Discrete Random Variable 6
Discrete Random Variable 7
Continuous Random Variable 1
Continuous Random Variable 2
Continuous Random Variable 3
Continuous Random Variable 4
Continuous Random Variable 5
Continuous Random Variable 6
Continuous Random Variable 7
Joint Probability Distributions
Discrete Joint Random Variables
Discrete Joint RV Example
Marginal PMF and CDF for Discrete Joint RV
Conditional PMF and CDF for Discrete Joint RV
Continuous Joint Random Variables
Marginal PDF and CDF for Continuous Joint RV
Conditional PDF and CDF for Continuous Joint RV
Mathematical Expectation & Variance
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
Expected Value and Variance for Continuous Joint RV
Covariance and Correlation Coefficient
Covariance
Example 1
Example 2
Example 3
Variance of Sums
Example 4
Correlation Coefficient
Example 5
Sample Midterm Problems III
Discrete Random Variable 1- Expected Value
Discrete Random Variable 2 - Expected Value
Discrete Random Variable 3 - Variance
Discrete Random Variable 4- Expected Value
Discrete Random Variable 5 - Expected Value
Discrete Random Variable 6 - Expected Value and Variance
Continuous Random Variable 1 - Expected Value
Continuous Random Variable 2 - Expected Value
Continuous Random Variable 3 - Variance
Continuous Random Variable 4 - Expected Value
Continuous Random Variable 5 - Expected Value and Variance
Discrete Joint Distribution 1
Discrete Joint Distribution 2
Discrete Joint Distribution 3
Continuous Joint Distribution 1
Continuous Joint Distribution 2
Continuous Joint Distribution 3
Continuous Joint Distribution 4
Covariance 1
Covariance 2
Covariance 3
Correlation Coefficient
Some Discrete Probability Distributions
Chebyshev's Inequality
Example
Bernoulli Distribution Part 1
Bernoulli Distribution Part 2
Example 1
Example 2
Binomial Distribution Part 1
Binomial Distribution Part 2
Example 3
Example 4
Hypergeometric Distribution
Example 5
Some Continuous Probability Distributions
Uniform Distribution
Example 1
Example 2
Normal Distribution
Standard Normal Distribution
Reading Z Table - Option 1
Reading Z Table - Option 2
Example 3
Sample Midterm Problems IV
Chebyshev's Theorem
Binomial Distribution 1
Binomial Distribution 2
Binomial Distribution 3
Binomial Distribution 4
Hypergeometric Distribution 1
Hypergeometric Distribution 2
Hypergeometric Distribution 3
Hypergeometric Distribution 4
Uniform Distribution 1
Uniform Distribution 2
Uniform Distribution 3
Normal Distribution 1
Normal Distribution 2
Normal Distribution 3
Normal Distribution 4
Normal Distribution 5
Normal Distribution 6
Normal Distribution 7
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.