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Statistical Methods are widely used in Medical, Biological, Clinical, Business and Engineering field. The data which form the basis for the statistical methods helps us to take scientific and informed decisions. Statistical methods deal with the collection, compilation, analysis and making inference from the data. The book mainly focuses on non-parametric aspects of Statistical methods. Non parametric methods or tests are used when the assumption about the distribution of the variables in the data set is not known or does not follow normal distribution assumption. Non parametric methods are useful to deal with ordered categorical data. When the sample size is large, statistical tests are robust due to the central limit theorem property. When sample size is small one need to use non-parametric tests. Compared to parametric tests, non-parametric tests are less powerful i.e. if we fail to reject the null hypothesis even if it is false. When the data set involves ranks or measured in ordinal scale then non-parametric tests are useful and easy to construct than parametric testsThe book uses open source R statistical software to carry out different non-parametric statistical methods with sample datasets.
Statistical methods are now widely used in different fields such as Business and Management, Economics, Biological, Physical sciences and including the new fields such as Data Science and Machine Learning. The data which form the basis for the statistical methods helps us to take scientific and informed decisions. Statistical methods deal with the collection, compilation, analysis and making inference from the data.This book deals with the statistical methods which are useful in Business and Management decision making. The methods include Probability, Sampling, Correlation, Regression and Hypothesis Testing, Time Series, Forecasting and Non-Parametric tests and advanced statistical models. The book uses open source R statistical software to carry out different statistical analysis with sample datasets. This book is third in series of Statistics books by the Author. Some of the contents are adopted from the author's previous statistical book introduction to statistical methods and non-parametric methods.
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