PPT-Using Simulation to Introduce Inference for Regression

By Josh Tabor Canyon del Oro High School Oro Valley AZ joshtaborhotmailcom Using Simulation to Introduce Inference for Regression Randomization tests are growing in popularity as an alternative to traditional tests but also as a way to help students to understand the logic of inference In this webinar we will use Fathom software and online applets to introduce inference for the slope of a leastsquares regression line. Introduction. Course Information. Your instructor: . Hyunseung. (pronounced Hun-Sung). Or HK (not Hong Kong . ). E-mail. : khyuns@wharton.upenn.edu . Lecture:. Time: Mon/Tues/Wed/. Thur. . at 10:45AM-12:15PM. Professor William Greene. Stern School of Business. IOMS Department . Department of Economics. Inference and Regression. Part . 9 – Linear Model Topics. Agenda. Variable Selection – Stepwise Regression. 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.. . and Randomization Procedures. Dennis Lock. Statistics Education Meeting. October 30, 2012. 1. An introductory statistics book writing with my family. Robin H. Lock (St. Lawrence). Patti F. Lock (St. Lawrence). 9E.1. : . Inference Testing for Linear Regression. To test claims and make inferences based off of linear regression analyses. Objective:. Introduction . Recall the . two-sample inference tests from the previous chapters. . Patti Frazer Lock Kari Lock Morgan. Cummings Professor of Mathematics Assistant Professor of the Practice. St. Lawrence University Duke University. AMATYC. November, 2012. The Lock. 5. Allan Rossman. Cal Poly – San Luis Obispo. arossman@calpoly.edu. http://statweb.calpoly.edu/arossman/. Advertisement. I will present a longer, more interactive version of this in a workshop on Saturday afternoon in Lincoln room. Patti Frazer Lock Kari Lock Morgan. Cummings Professor of Mathematics Assistant Professor of the Practice. St. Lawrence University Duke University. AMATYC. November, 2012. The Lock. 5. Stat-GB.3302.30, UB.0015.01. Professor William Greene. Stern School of Business. IOMS Department . Department of Economics. Statistical Inference and Regression Analysis. Part 0 - Introduction. . Professor William Greene; Economics and IOMS Departments. 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 = . Chapter 27: . Inference Testing for Linear Regression. To test claims and make inferences based off of linear regression analyses. Objective:. Introduction . Recall the . two-sample inference tests from the previous chapters. . Allan Rossman and Beth Chance. Cal Poly – San Luis Obispo. arossman@calpoly.edu. bchance@calpoly.edu. 2. AMATYC webinar April 2016. 2. Outline. Who are you?. Overview, motivation. Three examples. A. Patti Frazer Lock Kari Lock Morgan. Cummings Professor of Mathematics Assistant Professor of the Practice. St. Lawrence University Duke University. AMATYC. November, 2012. The Lock. 5. Thomas Jonsson. Why? What’s needed?. Automated testing of many test cases is a requirement to avoid regressions.. Automated . testing is also needed for Continuous Integration.. Recording the provenance of regression test cases is important to be able to repeat the the reference simulation..