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Course content
Sections:
1
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Activities:
1
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Resources:
61
- Announcements
- 001 INTRODUCTION TO THE COURSE The Key Concepts and Software Tools TfEk gitir
- 003 Difference Between Statistical Analysis Machine Learning JQrh gitir
- 004 Getting Started with R and R Studio StbE gitir
- 005 Reading in Data with R 11Dc gitir
- 006 Data Cleaning with R CfWS gitir
- 007 Some More Data Cleaning with R Sc3L gitir
- 008 Basic Exploratory Data Analysis in R ZzI8 gitir
- 009 Conclusion to Section 1 5cIb gitir
- 010 OLS Regression Theory CJ8S gitir
- 011 OLS Implementation 5V1n gitir
- 012 More on Result Interpretations MRn2 gitir
- 013 Confidence Interval Theory abjh gitir
- 014 Calculate the Confidence Interval in R asTA gitir
- 015 Confidence Interval and OLS Regressions 5WD0 gitir
- 016 Linear Regression without Intercept Uner gitir
- 017 Implement ANOVA on OLS Regression fRv1 gitir
- 018 Multiple Linear Regression zmc5 gitir
- 019 Multiple Linear regression with Interaction and Dummy Variables 6nPl gitir
- 020 Some Basic Conditions that OLS Models Have to Fulfill mAMA gitir
- 021 Conclusions to Section 2 F8gG gitir
- 022 Identify Multicollinearity F29K gitir
- 023 Doing Regression Analyses with Correlated Predictor Variables MviS gitir
- 024 Principal Component Regression in R Gj7G gitir
- 025 Partial Least Square Regression in R XYIg gitir
- 026 Ridge Regression in R g3co gitir
- 027 LASSO Regression bEu0 gitir
- 028 Conclusion to Section 3 xXI9 gitir
- 029 Why Do Any Kind of Selection fvNZ gitir
- 030 Select the Most Suitable OLS Regression Model iVcy gitir
- 031 Select Model Subsets mpAU gitir
- 032 Machine Learning Perspective on Evaluate Regression Model Accuracy 8xtX gitir
- 033 Evaluate Regression Model Performance 9FEY gitir
- 034 LASSO Regression for Variable Selection 2WJM gitir
- 035 Identify the Contribution of Predictors in Explaining the Variation in Y 3yKI gitir
- 036 Conclusions to Section 4 m1Zs gitir
- 037 Data Transformations yWhN gitir
- 038 Robust Regression Deal with Outliers h3e4 gitir
- 039 Dealing with Heteroscedasticity 3yii gitir
- 040 Conclusions to Section 5 n6kc gitir
- 041 What are GLMs QJB5 gitir
- 042 Logistic regression ImIe gitir
- 043 Logistic Regression for Binary Response Variable a45Y gitir
- 044 Multinomial Logistic Regression DgDd gitir
- 045 Regression for Count Data 7HAN gitir
- 046 Goodness of fit testing RhJZ gitir
- 047 Conclusions to Section 6 Pox2 gitir
- 049 Polynomial and Non linear regression cwl9 gitir
- 050 Generalized Additive Models GAMs in R 1iXg gitir
- 051 Boosted GAM Regression YOZm gitir
- 052 Multivariate Adaptive Regression Splines MARS oQIq gitir
- 054 CART Regression Trees in R B1no gitir
- 055 Conditional Inference Trees DUuv gitir
- 056 Random Forest RF CBvp gitir
- 057 Gradient Boosting Regression xRMi gitir
- 058 ML Model Selection 9unN gitir
- 059 Conclusions to Section 7 BAnF gitir
- 060 Read in DTA Extension File iZhD gitir
- 061 Getting Acquainted with Github Desktop LiBK gitir
- 062 Using R Colab Up3S gitir
- 063 Group By Time MPzC gitir
- 064 POSIT 58IB gitir