Winter 2013 Quantitative Methods for Lawyers Course
Professor Daniel Martin Katz
Michigan State University – College of Law
(1) Office Hours : 3:15-4:15 Wednesday in 230F Law College Building (or by Appt.)
(2) Syllabus for Winter 2013 – Quantitative Methods for Lawyers Course (V1.04)(Updated 4/15/13)
(5) Teams for the Simulation
(6) Expert Qualifications
(7) Introduction to the Course + Research Design Part I (Class #1)
(8) Research Design Part II (Class #2)
(9) Research Design Part III (Class #3)
(10) Research Design Part IV (Class #4)
(11) Research Design Part V (Class #5)
(12) Four Scientific Evidence Cases for 1/23/12
Daubert Case (Access via Cornell LII)
Frye Case (Access via Harvard)
Illinois v. LIPSCOMB
US v. Starzecpyzel, 880 F. Supp. 1027 (1995)
Cross Examination Training Video (Link has been emailed to you)
(13) Introduction to Probability & Basic Statistics (Part I) (Class #6)
(14) Introduction to Probability & Basic Statistics (Part II) (Class #7)
(15) Introduction to Probability & Basic Statistics (Part III) (Class #8)
(16) Conditional Probability and Bayes Rule (Class #9)
(17) Bayes Rule and Sampling (Class #10)
(18) Skewness, Kurtosis & Binomial Distributions (Class #11)
(19) The Normal Distribution, Power Laws and Z-Scores (Class #12)
(20) Quantitative Methods for Lawyers – Problem Set #1
(21) Hypothesis Testing & Statistical Significance (Class #13)
(22) Chi Square Test (Class #14)
(23) Students “T” Distribution (Class #15)
(24) Quantitative Methods for Lawyers – Problem Set #2
download states.dta file
(25) Intro to STATA, More T Stat, F-Statistic & ANOVA (Class #16)
(26) Covariance, Correlation & Intro to Regression (Class #17)
(27) Regression Analysis – Part I (Class #18)
(28) Regression Analysis – Part II (Class #19)
(29) Quantitative Methods for Lawyers – Problem Set #3
download hprice1981.dta
(30) Regression Analysis -Part III (Class #20)
(31) Final Project Assignment (Due on or before 2pm – May 1st, 2013)
crime1.dta
pension.dta
smoke.dta
attend.dta
Access Info about Each Dataset Here:
http://fmwww.bc.edu/ec-p/data/wooldridge/datasets.list.html
(32) Regression Analysis IV (Class#21)
(33) Regression Analysis V (Class#22)
(34) Preview of Future Course: Algorithmic Thinking, Inverse Problems, Analogical Reasoning and the Science of Similarity (Class#23)
