Data 621- Business Analytics and Data Mining

Reading:

• Book - A Modern Approach to Regression with R.

• Book - Linear Models with R.

Home works:

• https://github.com/akarimhammoud/Data_621

Week 1: Introduction to Applied Regression Modeling

Assumptions of Linear regression - https://youtu.be/kxq2jX4qC28

Linear regression - https://youtu.be/zPG4NjIkCjc

Week 2: Simple Linear Regression: Estimation

• File Source: “Lab: Linear Regression,” Trevor Hastie and Rob Tibshirani, from Stanford course on Statistical Learning, Stanford 2014. Hands on R Labs that also covers multiple linear regression. https://bbhosted.cuny.edu/bbcswebdav/pid-58499819-dt-content-rid-463188831_1/xid-463188831_1

• Dummy Variables,” INCAE Business School, https://www.youtube.com/watch?v=9yTui_LoSOc.

Week 3: Simple Linear Regression: Inference, Prediction, Explanation

• Linear Regression for Prediction, Brian Caffo, https://www.youtube.com/watch?v=5isJA7T5_VE

Week 4: Simple Linear Regression: Diagnostics and Transformations

• Simple Linear Regression: Checking Assumptions with Residual Plots, jbstatistics, https://www.youtube.com/watch?v=iMdtTCX2Q70

• Simple Linear Regression: Transformations, jbstatistics, https://www.youtube.com/watch?v=HIcqQhn3vSM

• Statistics with R: Box-Cox transformation of the response in a linear model part 1, Phil Chan, https://www.youtube.com/watch?v=TgVx9Rqsewo

• Statistics with R: Box-Cox transformation of the response in a linear model part 2, Phil Chan, https://www.youtube.com/watch?v=6O_9QUeyBVU

Week 5: Multiple Linear Regression and Missing Data

• Features and Polynomial Regression,” Andrew Ng, https://www.coursera.org/learn/machine-learning/lecture/Rqgfz/features-and-polynomial-regression

• https://www.youtube.com/watch?v=lo7KnnvyEU0&list=PL5-da3qGB5IBSSCPANhTgrw82ws7w_or9&index=6

• Model Selection and Qualitative Predictors”, Statistical Learning (Stanford’s Trevor Hastie and Rob Tibshirani), https://www.youtube.com/watch?v=3T6RXmIHbJ4, ### Week 6: Multiple Linear Regression: Diagnostics and Transformations

• Checking Multiple Regression Diagnostics Using Graphs,” OpenIntro.org, https://www.youtube.com/watch?list=PLkIselvEzpM5f1HYzIjFt52SD4izsJ2_I&v=3KSUeYMKt5A

• Residuals, Diagnostics, and Variation,” Part 1/3, Brian Caffo, https://www.youtube.com/watch?v=VohfwSJuG4k. Covers influential, high leverage, and outlying points.

Week 7: Variable Selection and Shrinkage Methods

• Bias-variance in model selection, https://www.youtube.com/watch?v=W0NLs-A6hhQ, mathematical monk, Jul 2, 2011

• Lab: Best subset selection,” Trevor Hastie and Rob Tibshirani, from Stanford course on Statistical Learning, Stanford 2014. https://www.youtube.com/watch?v=3kwdDGnV8MM. Hands on R Labs that also covers multiple linear regression.

Week 8: Binary Logistic Regression

• Generalized Linear Models,” Brian Caffo, https://www.youtube.com/watch?v=xEwM1nzQckY. July 27, 2015

• Lab: Logistic Regression,” Trevor Hastie and Rob Tibshirani, from Stanford course on Statistical Learning, Stanford 2014. https://www.youtube.com/watch?v=TxvEVc8YNlU

• Discrete choice models - introduction to logit and probit,” Ben Lambert, https://www.youtube.com/watch?v=yPCQZeGWJjw.

• Probit and Logit Models,” Ani Katchova, https://www.youtube.com/watch?v=1cFYlMjEz-c,

• Probit and Logit Models Example,” Ani Katchova, https://www.youtube.com/watch?v=66Mn9GAWrAE&t=8s

• Probit and Logit Models in R,” Ani Katchova, https://www.youtube.com/watch?v=A9P888Lxde8.

• Code and data at https://sites.google.com/site/econometricsacademy/econometrics-models/probit-and-logit-models

Week 9: Count Regression

• Poisson regression, part 1 of 2,” Brian Caffo, https://www.youtube.com/watch?v=YtotMuVmOUM

• Poisson regression, part 2 of 2,” https://www.youtube.com/watch?v=hg51LjG1xIc

Week 10: Weighted Least Squares and Robust Regression

• Weighted Least Squares: an introduction, Ben Lambert, https://www.youtube.com/watch?v=wCJ8I-MtJdQ

• Weighted Least Squares: mathematical introduction,” Ben Lambert, https://www.youtube.com/watch?v=nNRcJgKSpjg

• Weighted Least Squares: an example,” Ben Lambert, https://www.youtube.com/watch?v=Ghs69kGWwAA

• GG413: Weighted Least Squares Regression,” Garrett Apuzen-Ito [University of Hawaii], https://www.youtube.com/watch?v=VbMeWUsQdog

• Robust Regression with Huber Weighting,” Maths Resource, https://www.youtube.com/watch?v=0drbiDPCuYQ

Week 11: Generalized Least Squares

• Statistics with R (3) - Generalized, linear, and generalized least squares models (LM, GLM, GLS),” Christophe Sherber, https://www.youtube.com/watch?v=P-WYkSZp9lY

• Least squares I: Matrix problems,” Lorenzo Sadun [University of Texas], https://www.youtube.com/watch?v=Z0wELiinNVQ

• Least Squares II: Linear Regression,” Lorenzo Sadun [University of Texas], https://www.youtube.com/watch?v=Lx6CfgKVIuE

• Least Squares III: Multiple Regression and Curve Fitting,” Lorenzo Sadun [University of Texas], https://www.youtube.com/watch?v=CLHHzB9lPaE.

Week 12: Multinomial Logistic Regression

• Econometrics - Multinomial Probit and Logit Models,” Ani Katchova, https://www.youtube.com/watch?v=__wQLMuax00

• Multinomial Probit and Logit Models Example,” Ani Katchova, https://www.youtube.com/watch?v=ZrgOb--Xnkg

• Multinomial Probit and Logit Models in R,” https://www.youtube.com/watch?v=-Cp_KP9mq94, Ani Katchova

• Code and data at https://sites.google.com/site/econometricsacademy/econometrics-models/multinomial-probit-and-logit-models

• An Intuitive Introduction to the Multinomial Logit,” Doug McKee, https://www.youtube.com/watch?v=n7zHXjuE6PE

• Additional reading about Possion and Negative Binomial Distribution

Week 13: Generalized Linear Models

• Poisson distribution: a member of the exp family,” Deirdre Toher, [University of the West of England], https://www.youtube.com/watch?v=VFZ8b_xeTKc

• Binomial distribution: in the exponential family,” Deirdre Toher, [University of the West of England], https://www.youtube.com/watch?v=7mNrsFr7P_A

• Binomial Distribution 2: Canonical Link function,” Deirdre Toher, [University of the West of], https://www.youtube.com/watch?v=MfynxwNqgfU

• Normal distribution: in the exponential family,” Deirdre Toher, [University of the West of England], https://www.youtube.com/watch?v=ZZfOVutsIY0

• Gamma Distribution: Member of the Exp Family,” Deirdre Toher, [University of the West of England], https://www.youtube.com/watch?v=KZkR5i0zoSQ

Week 14: Panel Regression: Repeated Measures and Longitudinal Data

• Mixed effects models with R,” Christoph Scherber, https://www.youtube.com/watch?v=VhMWPkTbXoY

• Fixed Effects vs Random Effects,” BurkeyAcademy, https://www.youtube.com/watch?v=ySTb5Nrhc8g

• Panel Data Models with Individual and Time Fixed Effects,” BurkeyAcademy, https://www.youtube.com/watch?v=pQvhi60yN74

Week 15: Nonparametric Regression

• Kernel Density Estimation and Kernel Regression,” Justin Esarey [Rice University], https://www.youtube.com/watch?v=QSNN0no4dSI

• 5.2.7-Curve Fitting: Spline Interpolation,” Jacob Bishop, https://www.youtube.com/watch?v=dxvmafuP9Wk