QMBU 301 • Final • Quantitative Methods in Business
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Fatma Doğan
İşletme
QMBU 301 zor derstir, biliriz.
QMBU 301 Final'i için hazırlanmış bu dersimizde Time Series ve türevlerini görüp, çıkmış sınav sorularıyla antreman yapabileceksin
Eğitmen
Metin Eraslan
Eğitmen
Merhaba 2006 yılından bu yana üniversitelerin yabancı dilde eğitim veren Ekonomi ve İşletme fakültelerindeki öğrencilerine yardımcı olmaktayım. 20 yıllık tecrübem ve kendime has anlatım tekniklerim ile her üniversite ve ders hocasını ayrı ayrı ele alarak sınavlarda doğrudan hedefe yönelik çalışmalar yapmaktayım.
Paketi Tamamla
🎓 Koç Üniversitesinde öğrencilerin %92'si tüm paketi alarak çalışıyor.
QMBU 301 • Midterm
Quantitative Methods in Business
Metin Eraslan
1999 TL
QMBU 301 • Final
Quantitative Methods in Business
Metin Eraslan
1999 TL
Konular
Multiple Linear Regression
Multiple Linear Regression Model
Multiple Linear Regression - Örnek 1
Multiple Linear Regression - Örnek 2 (Part 1)
Multiple Linear Regression - Örnek 2 (Part 2)
Multiple Linear Regression - Örnek 3
Multiple Linear Regression - Örnek 4
Assumptions of Linear Regression Model
Multicollinearity
Assumptions of Linear Regression Model - An Introduction
Assumptions of Linear Regression Model - Detailed
Assumptions of Linear Regression Model - Summary
Tukey's Bulging Rule
Assumptions of Linear Regression Model - Örnek
Sample Quiz
Sample Quiz 2
Exam Like Questions: Regression Model
Exam Like Question 1 - Part 1
Exam Like Question 1 - Part 2
Exam Like Question 1 - Part 3
Exam Like Question 1 - Part 4
Exam Like Question 2
Exam Like Question 3
Exam Like Question 4
Exam Like Question 5
Exam Like Question 6
Exam Like Question 7
Autocorrelation
Residual Autocorrelation Nedir? Durbin Watson Test Nedir, Nasıl Uygulanır?
Residual Autocorrelation and DW Test - Exam Like Question
Autocorrelation between Y's
Autocorrelation between Y's - Exam Like Question
Forecasting with Time Series - Intro
Başlarken Önemli Tüyo
Basic Concepts: Trend Vs Stationary & Seasonality Vs Cycle
Time Series Forecasting Techniques - An Overview
Time Series Tecniques for "Stationary + No Seasonality"
Naive Method
Simple Averaging
Moving Average
Simple Exponential Smoothing
Sample Quiz
Question 1
Question 2
Question 3
Question 4
Time Series Tecniques for "Trend + No Seasonality"
Naive Method with Trend
Double Moving Average
Exam Like Question
Holt's Method (Double Exponential Smoothing)
Regression Based Trend Models
Time Series Tecniques for "Seasonality + No Trend"
Winter's Additive Method
Winter's Multiplicative Method
Regression Based Seasonality Models
Time Series Tecniques for "Trend + Seasonality"
Holt-Winter's Additive Method
Holt-Winter's Multpicative Method
Regression Based "Trend+Seasonality" Methods
Regression Based "Trend+Seasonality Methods" - Örnek
Decomposition
Decomposition - Örnek 1
Decomposition - Örnek 2
Decomposition - Örnek 3
Decision Trees
Basic Probability (Temel Olasılık)
Baye's Theorem
How to Built a Decision Tree?
Exam Like Question 1
Exam Like Question 2
Değerlendirmeler
Ders İçeriği
Multiple Linear Regression
Multiple Linear Regression Model
Multiple Linear Regression - Örnek 1
Multiple Linear Regression - Örnek 2 (Part 1)
Multiple Linear Regression - Örnek 2 (Part 2)
Multiple Linear Regression - Örnek 3
Multiple Linear Regression - Örnek 4
Assumptions of Linear Regression Model
Multicollinearity
Assumptions of Linear Regression Model - An Introduction
Assumptions of Linear Regression Model - Detailed
Assumptions of Linear Regression Model - Summary
Tukey's Bulging Rule
Assumptions of Linear Regression Model - Örnek
Sample Quiz
Sample Quiz 2
Exam Like Questions: Regression Model
Exam Like Question 1 - Part 1
Exam Like Question 1 - Part 2
Exam Like Question 1 - Part 3
Exam Like Question 1 - Part 4
Exam Like Question 2
Exam Like Question 3
Exam Like Question 4
Exam Like Question 5
Exam Like Question 6
Exam Like Question 7
Autocorrelation
Residual Autocorrelation Nedir? Durbin Watson Test Nedir, Nasıl Uygulanır?
Residual Autocorrelation and DW Test - Exam Like Question
Autocorrelation between Y's
Autocorrelation between Y's - Exam Like Question
Forecasting with Time Series - Intro
Başlarken Önemli Tüyo
Basic Concepts: Trend Vs Stationary & Seasonality Vs Cycle
Time Series Forecasting Techniques - An Overview
Time Series Tecniques for "Stationary + No Seasonality"
Naive Method
Simple Averaging
Moving Average
Simple Exponential Smoothing
Sample Quiz
Question 1
Question 2
Question 3
Question 4
Time Series Tecniques for "Trend + No Seasonality"
Naive Method with Trend
Double Moving Average
Exam Like Question
Holt's Method (Double Exponential Smoothing)
Regression Based Trend Models
Time Series Tecniques for "Seasonality + No Trend"
Winter's Additive Method
Winter's Multiplicative Method
Regression Based Seasonality Models
Time Series Tecniques for "Trend + Seasonality"
Holt-Winter's Additive Method
Holt-Winter's Multpicative Method
Regression Based "Trend+Seasonality" Methods
Regression Based "Trend+Seasonality Methods" - Örnek
Decomposition
Decomposition - Örnek 1
Decomposition - Örnek 2
Decomposition - Örnek 3
Decision Trees
Basic Probability (Temel Olasılık)
Baye's Theorem
How to Built a Decision Tree?
Exam Like Question 1
Exam Like Question 2
Sıkça 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.