PPT-Regression Part II

Onefactor ANOVA Another dummy variable coding scheme Contrasts Multiple comparisons Interactions One factor Analysis of variance Categorical Explanatory variable Quantitative Response variable. isavectorofparameterstobeestimatedand x isavectorofpredictors forthe thof observationstheerrors areassumedtobenormallyandindependentlydistributedwith mean 0 and constant variance The function relating the average value of the response to the pred Professor William Greene. Stern School of Business. IOMS Department . Department of Economics. Statistics and Data Analysis. Part . 6 – Regression Model-1. Conditional Mean . U.S. Gasoline Price. Professor William Greene. Stern School of Business. IOMS Department. Department of Economics. Statistics and Data Analysis. Part . 10 . – . Qualitative Data. Modeling Qualitative Data. A Binary Outcome. This Talk Will:. I. ntroduce the history and logic of RDD,. Consider conditions for its internal validity,. Considers its sample size requirements, . Consider its dependence on functional form,. Illustrate some specification tests for it,. Design. Basics. Two potential outcomes . Yi(0) . and. Yi(1), . causal effect . Yi(1) − Yi(0), . binary treatment indicator . Wi. , . covariate. Xi, . and the observed outcome equal to:. At . Xi = c . Greg Cox. Richard Shiffrin. Continuous response measures. The problem. What do we do if we do not know the functional form?. Rasmussen & Williams, . Gaussian Processes for Machine Learning. http://www.gaussianprocesses.org/. Xi Chen. Machine Learning Department. Carnegie Mellon University. (joint work with . Han Liu. ). . Content. Experimental Results. Statistical Property . Multivariate Regression and Dyadic Regression Tree. Professor William Greene. Stern School of Business. IOMS Department. Department of Economics. Regression and Forecasting Models . Part . 7 . – . Multiple Regression. Analysis. Model Assumptions. SIT095. The Collection and Analysis of Quantitative Data II. Week 7. Luke Sloan. About Me. Name: Dr Luke Sloan. Office: 0.56 . Glamorgan. Email: . SloanLS@cardiff.ac.uk. To see me: . please email first. Linear Regression. Section 3.2. Reference Text:. The Practice of Statistics. , Fourth Edition.. Starnes, Yates, Moore. Warm up/ quiz . Draw a quick sketch of three scatterplots:. Draw a plot with r . An Application. Dr. Jerrell T. Stracener, . SAE Fellow. Leadership in Engineering. EMIS 7370/5370 STAT 5340 :. . . PROBABILITY AND STATISTICS FOR SCIENTISTS AND ENGINEERS. Systems Engineering Program. Professor William Greene. Stern School of Business. IOMS Department . Department of Economics. Inference and Regression. Perfect Collinearity. Perfect Multicollinearity. If . X. does not have full rank, then at least one column can be written as a linear combination of the other columns.. NBA 2013/14 Player Heights and Weights. Data Description / Model. Heights (X) and Weights (Y) for 505 NBA Players in 2013/14 Season. . Other Variables included in the Dataset: Age, Position. Simple Linear Regression Model: Y = . : A British biometrician, Sir Francis Galton, defined regression as ‘stepping back towards the average’. He found that the offspring of abnormally tall or short parents tends to regress or step back to average..