Mathematics

Statistics and Data
Science 363

Introduction to
Statistical Methods

Spring 2019

Resources

**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.

·
Rstudio is an integrated development environment
for R.

·
The Jupyter Notebook is an open-source web application that
allows you to create and share documents that contain live code, equations,
visualizations and narrative text.

- Tinn-R
is a Windows-based free, simple but efficient replacement for the basic
code editor provided by R-gui.
- knitr
integrates R code into a latex document.
- R snippets
allows you to run R in an internet browser.
- 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**