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Elementary Statistical Methods
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Elementary Statistical MethodsНазвание: Elementary Statistical Methods
Автор: Sahana Prasad
Издательство: Springer
Год: 2023
Страниц: 318
Язык: английский
Формат: pdf
Размер: 10.2 MB

Statistics is basically a mathematical science wherein data is first collected, then analysed by using suitable tools, explanation/interpretation given, and then finally converted into a valid conclusion. Statistical techniques are used right from data collection to final measurement. Different experimental designs and survey sampling techniques help in obtaining the data while data quality is improvised by statisticians by using data cleaning techniques. Various forecasting and prediction tools are available for providing inferences. Statistical knowledge is a relevant discipline in various academic organizations—in social and natural sciences and in business set-ups and governmental organizations.

This is the first book of two volumes covering the basics of statistical methods and analysis. Significant topics include concepts of research and data analysis, descriptive statistics, probability and distributions, correlation and regression, and statistical inference. The book includes useful examples and exercises as well as relevant case studies for proper implementation of the discussed tools. This book will be a valuable text for undergraduate students of statistics, management, economics, and psychology, wanting to gain basic understanding of statistics and the usage of its various concepts.

There are a large number of user-friendly packages available to aid research. SPSS (renamed PASW) STATA, SAS, EXCEL, R, etc., are some other software which are used to analyse data. However, usage of these requires caution as they operate like other software packages on the principle of “garbage-in, garbage-out”. Thus, it is essential to use the right statistical tools and to have at least a basic knowledge of statistics before using software.

This book deals with the above issues with reference to statistical tools. It assumes that the reader has very elementary or no knowledge about statistical tools and tries to explain all concepts by using case studies. There is just enough theory to introduce the concept and then take the reader through a variety of case studies. These answer four main questions, namely what, why, how and when. All concepts are explained keeping these questions, which are likely to arise while understanding statistical concepts.

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