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The book starts with the basics of data analysis through non-statistical and non-mathematical assessments of error and uncertainty conditions. Experimental and maximum errors and the use of simple graphical methods are briefly described. Applying quick methods on data analysis such as frequency distributions, determination of standard errors, and applications of significance tests are explained. Special attention is given to the statistical quick methods where the range is preferred to traditional methods of calculation. The author notes that the quick methods have more practical applications in physics and engineering. The use of the quick methods of calculation is more precise in error estimation, confidence limits, and tests for outliers that the error is very negligible when applied to actual conditions. Dealing with errors of computation arising from rounding of values, and those arising from the use of slide rules and of the logarithm tables, is explained. The use of numerical methods (integration, differentiation, and interpolation) and graphical methods (like curve fitting) is briefly explained, with the author’s emphasis on choosing the simpler methods.
Sixth formers, engineering undergraduates, statisticians, and students of mathematics will find the information in this book useful.

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