Titlebook: Applied Statistics for Social and Management Sciences; Abdul Quader Miah Textbook 2016 Springer Science+Business Media Singapore 2016 Appl

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Applied Statistics for Social and Management Sciences

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https://doi.org/10.1007/978-3-642-67234-7ules and the levels of measurement are important because each statistical technique is appropriate for data measured only at certain levels. So levels of measurement are introduced. Analysis of data that may vary will depend on the variables. So types of variables according to suitability are introduced.

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https://doi.org/10.1007/978-3-319-41418-8tive statistics dealing with mean (arithmetic, geometric), median, and mode are explained. The technique for calculation of the “growth rates” and future projection is shown. Measures of dispersion of data are explained. Descriptive statistics entails central tendency of data.

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Separation and Solid-Phase Systems independence. Distributions of frequencies of different classes within two categorical variables are used to test the good fit or bad fit according to goodness-of-fit test. In the test of independence, two distributions in two categorical variables are tested whether they are related or not. Each is explained with the help of examples.

Autobiography

Effects of Substrate Inhibition,e these. Techniques in constructing several indices are shown. These include priority, satisfaction, agreement, performance, price, laspeyres, paasche price, fisher’s ideal price, quantity, total cost, cost of living, and standard of living indices. The technique for calculating rate of inflation is shown. The Rule of 70 is explained.

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https://doi.org/10.1007/978-3-642-67234-7Data are collected often in raw form. These are then not useable unless summarized. The techniques of presentation in tabular and graphical forms are introduced. Some illustrations provided are real-world examples. Graphical presentations cover bar chart, pie chart, histogram, frequency polygon, pareto chart, frequency curve and line diagram.

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Basics of Enzyme Immobilization,Inferential statistics involves drawing conclusion regarding population parameters based on sample data drawn from the same population. In the process probabilities are an inherent part. Probabilities along with their axioms are defined. Calculation of probabilities in different situations is different and is explained with examples.

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Separation and Solid-Phase SystemsParameters and statistics, estimation, estimators, and estimates are presented. Properties of estimators are explained and the central limit theorem is introduced. Point estimation and interval estimation are explained and distinguished. The techniques of calculating confidence intervals in various situations are shown.