Statistical Computing Using R Software

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By Vishwas R. Pawgi more
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Product Specifications

Publisher Nirali Prakashan All Mathematics books by Nirali Prakashan
ISBN 9789351648642
Author: Vishwas R. Pawgi
Number of Pages 206
Edition Third Edition
Available in all digital devices
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Statistical Computing Using R Software by Vishwas R. Pawgi
Book Summary:

Now-a-days Statistical analysis has become an important part of scientific reasoning. It is required in various fields such as agriculture, business, biology, ecology, education, engineering, fishery, forestry, geology, management, medicine psychology etc. Use of computers has become essential for large data sets. Several commercial packages for statistical analysis are available but they are very costly at initial stage as well as the annual renewal charges of such softwares are also very high .

R is a freely available software and its recent version can always be easily downloaded from the internet (Site address : www.r− However R software is basically not a menu driven software but it operates in interactive mode. Therefore while using R software one has to search for appropriate command or function for statistical calculations and for analyzing the data.

There are very few books available in the market on R software covering all basic topics required for analysis. However these books are costly. So we felt the necessity to prepare a book on R software which will be useful for students as well as to statistical consultants for data analysis.

This book written on R software covers all major topics required for data analysis. It is also useful for learning basics of R software. The book contains illustrative examples on each topic which help as a guideline to solve the exercises provided at the end of each chapter.

Audience of the Book :
This book Useful for B.Sc students.
Table of Contents:

1. Fundamentals of R

2. Sampling Methods

3. Diagrams and Graphs

4. Measures of Central Tendency

5. Measures of Dispersion

6. Moments, Skewness and Kurtosis

7. Probability and Probability Distributions

8. Correlation and Regression

9. Tests of Hypotheses

10. Analysis of Variance (ANOVA)

11. Non-parametric Test

12. Programming in R

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