Mathematics 363

Introduction to Statistical Methods

Fall 2017

Resources

 

Course Homepage

 

Downloads and web interfaces

_      The R Project for Statistical Computing. R, free statistical analysis package developed by Robert Gentleman and Ross Ihaka, is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S.

_      Tinn-R is a Windows-based free, simple but efficient replacement for the basic code editor provided by R-gui.

_      Rstudio is an integrated development environment for R.

_      knitr integrates R code into a latex document.

_      R FAQ Frequently Asked Questions on R

 

Ethics

_      Declaration on Profession Ethics in several languages from the International Statistical Institute

_      Ethical Guidelines for Statistical Practice from the American Statistical Association

 

Manuals

_      SimpleR: Using R for Introductory Statistics by John Verzani.

_      R for Beginners by Emmanuel Paradis.

_      Introductory Statistics with R (first edition) by Peter Dalgaard from the Springer Link.

 

Handouts and Guides

_      R as a basic statistical calculator for obtaining p-values and plotting probability distributions (6 page pdf file) by Bruce Walsh.

_      R reference card by Jonathan Baron.

_      R reference card by Tom Short.

_      R for Matlab users by Mathesaurus

 

Textbooks

_      Investigating Statistical Concepts, Applications, and Methods by Beth L. Chance and Allan J. Rossman

_      Stat 2 by Ann R. Cannon, George W. Cobb, Bradley A. Hartlaub, Julie M. Legler, Robin H. Lock, Thomas L. Moore, Allan J. Rossman , Jeffrey A. Witmer

_      Probability and Statistics by Morris H. DeGroot and Mark J. Schervish

_      Stats: Data and Models by Richard D. DeVeaux, Paul F. Velleman, David E. Bock

_      Practicing Statistics: Guided Investigations for the Second Course by Shonda Kuiper and Jeff Sklar

_      Stat Labs: Mathematical Statistics Through Applications by Deborah Nolan and Terry P. Speed

_      Mathematical Statistics and Data Analysis by John A. Rice

 

On-line Resources

_      Correlation and Regression by Philip B. Stark

_      Java Applets provided by James W. Hardin

_      Java applets for power and sample size by Russ Lenth

_      Receiver operator characteristic curve

_      Links to online resources

 

Tables

_      Normal Distribution

_      t Distribution

_      Chi-square Distribution