Logo

Statistical Treatment of Experimental Data

Large book cover: Statistical Treatment of Experimental Data

Statistical Treatment of Experimental Data
by

Publisher: McGraw Hill
ISBN/ASIN: 088133913X

Description:
Even with a limited mathematics background, readers can understand what statistical methods are and how they may be used to obtain the best possible results from experimental measurements and data. The author describes the physical bases on which statistical theories are developed, and derives from them useful mathematical results and formulas for the evaluation and analysis of experimental data. Special mathematical techniques are explained as they are needed.

Home page url

Download or read it online for free here:
Download link
(multiple PDF files)

Similar books

Book cover: Introduction to Statistical ThoughtIntroduction to Statistical Thought
by
Upper undergraduate or graduate book in statistical thinking for students with a background in calculus and the ability to think abstractly. The focus is on ideas and concepts, as opposed to technical details of how to put those ideas into practice.
(15419 views)
Book cover: Bayesian Methods for Statistical AnalysisBayesian Methods for Statistical Analysis
by - ANU Press
A book on statistical methods for analysing a wide variety of data. Topics: bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, finite population inference, biased sampling and nonignorable nonresponse, etc.
(5901 views)
Book cover: Applied Multivariate Statistical AnalysisApplied Multivariate Statistical Analysis
by - Springer
The authors present multivariate data analysis in a way that is understandable to non-mathematicians and practitioners confronted by statistical data analysis. The book has a friendly yet rigorous style. Mathematical results are clearly stated.
(21098 views)
Book cover: Foundations in Statistical ReasoningFoundations in Statistical Reasoning
by
Contents: Statistical Reasoning; Obtaining Useful Evidence; Examining the Evidence Using Graphs and Statistics; Inferential Theory; Testing Hypotheses; Confidence Intervals and Sample Size; Analysis of Bivariate Quantitative Data; Chi Square; etc.
(6068 views)