Statistical Treatment of Experimental Data
by Hugh D. Young
Publisher: McGraw Hill 1962
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.
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by Jamie DeCoster - University of Alabama
It is important to know how to understand statistics so that we can make the proper judgments when a person presents us with an argument backed by data. Data are numbers with a context. We must always keep the meaning of our data in mind.
by Peter Young - arXiv
These notes discuss, in a style intended for physicists, how to average data and fit it to some functional form. I try to make clear what is being calculated, what assumptions are being made, and to give a derivation of results.
by Borek Puza - 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.
by Sidney Tyrrell - BookBoon
This textbook is for people who want to know how to use SPSS for analyzing data. The author has considerable experience of teaching many such people and assumes they know the basics of statistics but nothing about SPSS, or as it is now known, PASW.