CE 303 • Midterm I • Introduction to Probability & Statistics for Civil Engineers
Her mühendisliğin temelinde var olan Olasılık ve İstatistik konularının uygulamalarını gördüğümüz bu derste: 1) Probability 2) Conditional Probability and Bayes' Rule 3) Discrete Random Variables and Mathematical Expectation 4) Continuous Random Variables and Mathematical Expectation 5) Joint Probability Distributions 6) Covariance konularını inceliyoruz.
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.
Geçme Garantisi
Derslerimize güveniyoruz. Olur da sınavlarına bizimle hazırlandığın halde dersten kalırsan, iade alabilirsin. Koşullar
Konular
Descriptive Statistics
12 konu anlatımı
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
Counting
14 konu anlatımı
Basic Principles of Counting
Counting Examples
Permutations
Permutations Example
Groups and Circular Permutation Example
Identical Objects Example 1
Identical Objects Example 2
Identical Objects Example 3
Combination
n choose r
Committee Example 1
Committee Example 2
Ball Example 1
Ball Example 2
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
27 soru
Counting 1
Counting 2
Counting 3
Counting 4
Axioms of Probability 1
Axioms of Probability 2
Axioms of Probability 3
Axioms of Probability 4
Axioms of Probability 5
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 and Mathematical Expectation
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
Continuous Random Variables and Mathematical Expectation
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
Sample Midterm Problems II
17 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
Continuous Random Variables 1
Continuous Random Variables 2
Continuous Random Variables 3
Continuous Random Variables 4
Continuous Random Variables 5
Continuous Random Variables 6
Joint Probability Distributions
18 konu anlatımı
Discrete Joint Random Variables
Discrete Joint RV Example
Marginal PMF and CDF for Discrete Joint RV
Conditional PMF and CDF for Discrete Joint RV
Expected Value for Discrete Joint RV
Variance for Discrete Joint RV
Example 8
Conditional Expectation for Discrete Joint RV
Example 9
Example 10
Continuous Joint Random Variables
Marginal PDF and CDF for Continuous Joint RV
Conditional PDF and CDF for Continuous Joint RV
Expected Value and Variance for Continuous Joint RV
Conditional Expectation for Continuous Joint RV
Example 11
Example 12
Example 13
Covariance and Chebyshev’s Theorem
8 konu anlatımı · 2 soru
Covariance
Example 1 (Discrete)
Example 2 (Continuous)
Example 3 (Continuous)
Exam Like Question 1
Exam Like Question 2
Variance of Sums
Example 4
Chebyshev's Theorem
Example 5
Sample Midterm Problems III
16 soru
Discrete Joint Distribution 1
Discrete Joint Distribution 2
Discrete Joint Distribution 3
Discrete Joint Distribution 4
Continuous Joint Distribution 1
Continuous Joint Distribution 2
Continuous Joint Distribution 3
Continuous Joint Distribution 4
Continuous Joint Distribution 5
Continuous Joint Distribution 6
Covariance 1
Covariance 2
Covariance 3
Covariance 4
Chebyshev's Theorem 1
Chebyshev's Theorem 2
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