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Ücretsiz Dersi AlIE 256 • Midterm • Statistics for Industrial Engineers
Bugüne kadar hazırlanmış en kapsamlı Uygulamalı İstatistik dersi ile karşınızdayız! Detaylı konu anlatımları, sayısız örnek soru ve sınav öncesi prova sorularıyla sınava eksiksiz gireceksin.
Bu dersimizde sunduğumuz içerikler sırasıyla: 1) Sampling Distributions 2) Estimator Properties 3) Estimator Derivation Methods 4) Interval Estimation of Single Population 5) Interval Estimation of Multiple Populations konularını derinlemesine anlayıp sınava hazırlanırken, final konularına da temel atıyoruz.
Konular
Descriptive 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
Sampling Distributions: Part 1
Sample Mean
Sample Variance
Example 1
Central Limit Theorem
Example 2
Example 3
Example 4
Example 5
Example 6
Normal Approximation to Binomial Distribution
Normal Approximation to Poisson Distribution
Sampling Distributions: Part 2
Reading Z Table
Reading T Table
Reading Chi Table
Reading F Table
Z Distribution
Example 1
Exam Like Question 1
Chi Square Distribution
Example 2
T Distribution
Example 3
Example 4
Exam Like Question 2
F Distribution
Example 5
Example 6
Exam Like Question 3
Chapter Summary
Sample Midterm Problems I
Z Distribution 1
Z Distribution 2
Z Distribution 3
Z Distribution 4
Z Distribution 5
Z Distribution 6
Z Distribution 7
Z Distribution 8
Z Distribution 9
Z Distribution 10
Normal Approximation to Binomial Distribution 1
Normal Approximation to Binomial Distribution 2
Normal Approximation to Binomial Distribution 3
T Distribution 1
T Distribution 2
T Distribution 3
Chi Square Distribution 1
Chi Square Distribution 2
Chi Square Distribution 3
Chi Square Distribution 4
Chi Square Distribution 5
F Distribution 1
F Distribution 2
All Distributions 1
All Distributions 2
Point Estimation (Properties)
Introduction
Unbiased Estimators 1
Unbiased Estimators 2
Exam like Question 1
Exam like Question 2
Exam like Question 3
Exam like Question 4
Exam like Question 5
Asymptotically Unbiased Estimators
Exam like Question 6
Efficient Estimators
Exam like Question 7
Exam Like Question 8
Exam Like Question 9
Consistent Estimators 1
Consistent Estimators 2
Consistent Estimators 3
Exam like Question 10
Sufficient Estimators 1
Sufficient Estimators 2
Exam Like Question 11
Chapter Summary
Point Estimation (Derivation Methods)
Method of Moments
Example 1
Example 2
Example 3
Example 4
Method of Maximum Likelihood
Example 5
Example 6
Example 7
Example 8
Chapter Summary
Sample Midterm Problems II
Unbiased Estimators 1
Unbiased Estimators 2
Unbiased Estimators 3
Unbiased Estimators 4
Consistent Estimator 1
Consistent Estimator 2
Unbiased and Consistent Estimator 1
Unbiased and Consistent Estimator 2
Efficient Estimators 1
Efficient Estimators 2
Maximum Likelihood Estimators 1
Maximum Likelihood Estimators 2
Method of Moments and MLE
Point Estimation - All Properties
Point Estimation 1 (High Level)
Point Estimation 2 (High Level)
Confidence Interval : Single Population
Introduction
Table Values
Confidence Interval for Means( Sigma known)
Example 1
Example 2
Example 3
Exam-like Question 1
Confidence Interval for Means (sigma unknown)
Example 1
Example 2
Confidence Interval for Proportions
Example 1
Example 2
Exam-like Question 1
Confidence Interval For Variances
Example 1
Example 2
Example 3
Exam like Question 1
Confidence Interval : Two Populations
Confidence Interval For Difference Between Means ( sigma known)
Example 1
Example 2
Exam-like Question 1
Confidence Interval For Difference Between Means ( sigma unknown)
Example 1
Example 2
Exam-like Question
Confidence Interval for Difference Between Proportions
Example 1
Example 2
Confidence Interval for Ratio of Variances
Example
Chapter Summary
Sample Midterm Problems III
Confidence Interval Summary
C.I. of Mean (Known Variance) 1
C.I. of Mean (Known Variance) 2
C.I. of Mean (Known Variance) 3
C.I. of Mean (Unknown Variance) 1
C.I. of Mean (Unknown Variance) 2
C.I. of Mean (Unknown Variance) 3
C.I. of Proportion 1
C.I. of Proportion 2
C.I. of Variance 1
C.I. of Variance 2
C.I. of Variance 3
C.I. of Difference of Means (Known Variances) 1
C.I. of Difference of Means (Known Variances) 2
C.I. of Difference of Means (Unknown Variances) 1
C.I. of Difference of Means (Unknown Variances) 2
C.I. of Difference of Means (Unknown Variances) 3
C.I. of Difference Between Proportions 1
C.I. of Differences Between Proportions 2
C.I. of Proportion of Variances 1
General Confidence Interval 1 ( High Level )
General Confidence Interval 2( High Level )
General Confidence Interval 3 ( High Level )
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. 11 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.
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