CE 202 • Tüm Sınavlar • Introduction to Probability and Statistics
Olasılıkla başlayıp, İstatistikle biten bu dersimizde özet ve uygulamaları konu anlatımlarıyla temelleri atıyor; sayısız çözümlü soru örneğiyle sınavlara hazır hale geliyoruz!
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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
Introduction to Statistics and Data Analysis
23 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
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
End of Topic Questions
6 soru
Data Analysis 1
Data Analysis 2
Data Analysis 3
Data Analysis 4
Data Analysis 5
Data Analysis 6
Basic Concept 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
End of Topic Questions
4 soru
Axioms of Probability 1
Axioms of Probability 2
Axioms of Probability 3
Axioms of Probability 4
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
End of Topic Questions
18 soru
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
6 konu anlatımı
Random Variables
Probability Mass Function
PMF Example 1
PMF Example 2
Cumulative Distribution Function
CDF Example 1
End of Topic Questions
9 soru
Discrete Random Variable 1
Discrete Random Variable 2
Discrete Random Variable 3
Discrete Random Variable 4
Discrete Random Variable 5
Discrete Random Variables 6
Discrete Random Variables 7
Discrete Random Variables 8
Discrete Random Variables 9
Continuous Random Variables
4 konu anlatımı
Probability Density Function - PDF
Example 1
Cumulative Distribution Function - CDF
Example 2
End of Topic Questions
7 soru
Continuous Random Variables 1
Continuous Random Variables 2
Continuous Random Variables 3
Continuous Random Variables 4
Continuous Random Variables 5
Continuous Random Variables 6
Continuous Random Variables 7
Joint Probability Distributions, Statistical Independence
7 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
Continuous Joint Random Variables
Marginal PDF and CDF for Continuous Joint RV
Conditional PDF and CDF for Continuous Joint RV
End of Topic Questions
6 soru
Discrete Joint Probability 1
Discrete Joint Probability 2
Discrete Joint Probability 3
Continuous Joint Probability 1
Continuous Joint Probability 2
Continuous Joint Probability 3
Mathematical Expected Value, Variance and Covariance
22 konu anlatımı
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
14 konu anlatımı
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
17 konu anlatımı
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
3 konu anlatımı
T Table
Chi Square Table
F Table
Sampling Distribution of Sample Mean and Sample Variance
7 konu anlatımı
Sample Mean
Sample Variance
Central Limit Theorem
Z Distribution
Chi Square Distribution
T Distribution
F Distribution
One and Two Sample Estimation
16 konu anlatımı
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
12 konu anlatımı
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
61 soru
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