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Probability Theory
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Title of the book
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Elementary Statistics: A Step by Step Approach (Written by Allan G. Bluman)
Probability and Statistics for Engineering and the Sciences (Written by Jay L Devore)
Introduction to Probability and Statistics (Written by William Mendenhall, Robert J Beaver, and Barbara M Beaver)
Introduction to Probability and Statistics for Engineers and Scientists (Written by Sheldon M. Ross)
A First Course in Probability (Written by Sheldon Ross)
Fundamentals of Mathematical Statistics (Written by S.C. Gupta, V.K. Kapoor)
An Introduction to Statistical Methods and Data Analysis (Written by R Lyman Ott and Michael Longnecker)
Statistics and Probability Theory (Written by Dr. K.C. Jain and Dr. M.L. Rawat)
Introduction to Probability (Written by Dimitri P. Bertsekas and John N. Tsitsiklis)
Business Statistics for Contemporary Decision Making (Written by Ken Black)
Introductory Statistics (Written by Sheldon M. Ross)
Introductory Statistics (Written by Douglas S Shafer and Zhiyi Zhang)
Managerial Statistics (Written by Gerald Keller)
Introduction to Mathematical Statistics (Written by Robert V. Hogg, Joseph W. Mckean, Allen T. Craig)
Mathematical Statistics and Data Analysis (Written by John A. Rice)
About the Book
About the Contributor
Author:
Jay L Devore
Title of the Book:
Probability and Statistics for Engineering and the Sciences
Publisher:
Richard Stratton, Boston, USA
Year:
2012
Edition:
8
ISBN:
9780538733526
Contributor Name:
Angela Paul, B.Tech., Computer Science and Engineering, Government Engineering College, Thrissur
Reviewer:
R TBC Team
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The generated PDF is not the PDF of the book as named but only is the PDF of the solved example for R
Title of the chapter
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1. Overview and descriptive statistics
2. Probability
3. Discrete random variables and probability distributions
4. Continuous random variables and probability distributions
5. Joint probability distributions and random samples
6. Point estimation
7. Statistical intervals based on a single sample
8. Test of hypotheses based on a single sample
9. Inferences based on two samples
10. The analysis of variance
11. Multifactor analysis of variance
12. Simple linear regression and correlation
13. Nonlinear and multiple regression
14. Goodness of fit tests and categorical data analysis
15. Distribution free procedures
16. Quality control methods
Example No. (Caption):
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