# Sachin Gadkar

## This page contains useful information and links for *Personal, SAS, Mathematics, Statistics, Finance and
Miscellaneous sites.*

### Personal Information

**1.**
This is my Personal Email Id.

__ sachin.gadkar@gmail.com __

**2.**
Here you can see my CV in doc format.

### SAS

** 1.**
SAS support site contains documentation and sample programs. This is particularly useful when we need to learn some part
of sas with examples.

**2.**
This is the finest resource of all the tutorials from SUG.

**3.**
Post and read queries on SAS, a very nice source to learn SAS with experts.

**4.**
Google groups which is same as listserv and good medium to learn SAS, C++, C and much more.

**5.**
Writing Efficient SAS Codes by Chong-ho (Alex) Yu. This site gives tips, codes on SAS.

**6.**
SAS code examples.

**7.**
Resources to help you learn SAS. It also contains links to regression, logistic regression, repeated measure analysis,
survey data analysis.

**8.**
Online documentation for SAS.

**9.**
This ring joins sites on the Web which have SAS� Software as their primary topic. SAS Software is used to build
statistical, EIS, MIS, Data warehouse and OLAP applications on PC, Mac, Unix and Mainframe platforms.

**10.**
SAS consultant special Interest group. Here you would get all the latest news in the sas world.

### MS Excel

**1.**
Excel Tutorial on Anthony's Web Page

### Mathematics

**1.**
IIT Bombay, Dept of Mathematics.

**2.**
PlanetMath.org nice site for Mathematical material

### Statistics

**-2.**
R 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. There are some important differences, but much code written for S runs unaltered under R.
R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity.
One of R's strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control

**-1.**
R Language mailing list archives

**0.**
This a nice introductory notes for beginners in R language.

**1.**
This is an ebook called the electronic textbook statsoft. A really nice and thorough SAS book.

**2.**
This is link to many online books on statistics.

**3.**
Online statistics textbook, Hyperstat online textbook.

**4.**
Stat Refresher index. This is an online reference which contains all the needed
statistical content. A really good one but the information is ordered in a tree structure, so you need to follow a link after link. The contents are clustering algorithms, correlation coefficient, Data Analysis, distributions, Expectations, linear regressions, measures of central tendency, Multiple regression, probability, variance and much more.

**5.**
This is online book, Basic principles of statistical Analysis. Focusses on GLM (general linear models)

**6.**
Basic introductory book nicely written and aimed at building mathematical models for real world. An extensive treatment of measurement and measurement scales as a model-building procedure.

**7.**
Multivariate statistics: Concepts Models and applications

**8.**
Data Mining introductory notes. It contains datamining introduction, Data mining functions, Data mining techniques, data mining examples.

**9.**
Statnotes : Topics in Multivariate Analysis, by David Garson.

**10.**
Little Handbook of Statistical Practice. Also contains a brief overview of logistic regression

**11.**
Online book in pdf of Probability theory by Grinstead and Snell

**12.**
Concepts and Applications of inferential statistics

**13.**
DMOZ web resources for statistics

**14.**
Complete guide to nonlinear regression

**15.**
A very nice tutorial on mathematical modelling

**16.**
Compendium of common probability distributions

### Programming Languages

**1.**
Python's a very good OOP language.

**2.**
Vaults of Parnassus website

**3.**
Programming resource site SourceForge.net

### Finance

**1.**
Financial Markets for all

**2.**
This site has lot many financial tutorials and a simulator.

### General Resource

**1.**
Free Encyclopedia Wikipedia

**2.**
Webster's online dictionary with multilingual thesaurus translation.

**3.**
Merriam websters online dictionary

### Search Engines

**1.**
Google search engine.

**2.**
Altavista, the mother of all search engines.

**3.**
All the web is here in alltheweb.com

**4.**
Accoona matata...its is new search engine.

**4.**
A seach engine for scientific information only. SCIRUS

### eMail

**1.**
Gmail.

**2.**
accenture mail access from outside the intranet.

**3.**
Yahoomail

**4.**
Orkut to be in contact with your friends.

### Official Site

**0.**
accenture consulting

**1.**
Cognizant technology solutions

**2.**
My blog

**3.**
My homepages

### Mathematics Teaching Downloads

**1.**
Notes that I prepared while teaching Mathematics at Jee level. These notes though are not complete
they contain few very nice conceptual things.

### SAS downloads

**1.**
Series #1 : This is the first notes made by me while learning SAS. Here we try to understand the input, put functions
in Base SAS, SCL functions inputc, inputn, putc, putn and the call execute routine.

**2.**
Series #2 : This is the second notes made by me. Here we try to understand the format and informat logic in SAS. Format
informat understanding is very important to code in SAS.

**3.**
Series #2 : This is the third in the series documented by me. In this pdf we try to understand the picture format used in the proc format.

**1.**
Connecting Two computers @Home with Just a Crossover Cable(Lan Cord)

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