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With Statistics for Management, Levin and Rubin have provided a non-intimidating business statistics book that users can easily read and understand. Like its predecessors, the seventh edition includes the absolute minimum of mathematical/statistical notation necessary to teach the material. Concepts are fully explained in simple, easy-to-understand language as they are presented, making the book an excellent source from which to learn and teach. After each discussion, readers are guided through real-world examples to show how book principles work in professional practice. Includes easy-to-understand explanations of difficult statistical topics, such as sampling distributions, relationship between confidence level and confidence interval, interpreting r-square. A complete package of teaching/learning aids is provided in every chapter, including chapter review exercises, chapter concepts tests,"Statistics at Work" conceptual cases, "Computer Database Exercises," "From the Textbook to the Real-World Examples." This ISBN is in two volumes Part A and Part B.
Teaches students how to apply statistics to real business problems through the authors' unique three-step approach to problem solving. Students learn to identify, compute and interpret the results in the context of the problem.
Statistical Analysis of Management Data provides a comprehensive approach to multivariate statistical analyses that are important for researchers in all fields of management, including finance, production, accounting, marketing, strategy, technology, and human resources. This book is especially designed to provide doctoral students with a theoretical knowledge of the concepts underlying the most important multivariate techniques and an overview of actual applications. It offers a clear, succinct exposition of each technique with emphasis on when each technique is appropriate and how to use it. This second edition, fully revised, updated, and expanded, reflects the most current evolution in the methods for data analysis in management and the social sciences. In particular, it places a greater emphasis on measurement models, and includes new chapters and sections on: confirmatory factor analysis canonical correlation analysis cluster analysis analysis of covariance structure multi-group confirmatory factor analysis and analysis of covariance structures. Featuring numerous examples, the book may serve as an advanced text or as a resource for applied researchers in industry who want to understand the foundations of the methods and to learn how they can be applied using widely available statistical software.
Primarily intended for the undergraduate and postgraduate students of management, the book can also be of immense help to the students of commerce, science and economics. The contents of the book cover the syllabi of various Indian universities and B-schools. The book is the outcome of the extensive teaching experience of the authors in various management schools. The text encompasses topics on descriptive statistics and averages, probability and Bayes’ theorem, distributions, sampling techniques, significance tests, chi-square tests and ANOVA. Besides, the book also acquaints the readers with the regression and correlation, and time series and index numbers. Distinguishing Features of the book • Statistics answers your questions in the beginning of each chapter outlines various areas of applications of statistics. • Various supplementary examples aid the students in gaining a thorough understanding of the discussed concept. • The case studies use real, recent and easily understandable data collected from various sources that acquaint the students with the real-life situations. • The self-test and exercises given at the end of each chapter test students’ comprehension of various underlying concepts and principles. • Answers to self-test and hints to exercises are also provided.
This book addresses the application of statistical techniques and methods across a wide range of disciplines. While its main focus is on the application of statistical methods, theoretical aspects are also provided as fundamental background information. It offers a systematic interpretation of results often discovered in general descriptions of methods and techniques such as linear and non-linear regression. SPSS is also used in all the application aspects. The presentation of data in the form of tables and graphs throughout the book not only guides users, but also explains the statistical application and assists readers in interpreting important features. The analysis of statistical data is presented consistently throughout the text. Academic researchers, practitioners and other users who work with statistical data will benefit from reading Applied Statistics for Social and Management Sciences.
This new text presents Mathematics and Statistics in a user friendly approach designed to meet the needs of students taking introductory courses in business, accountancy, finance and economics. A section is included to support students with weaker or rusty mathematics and provide additional reinforcement for stronger students. Every topic is illustrated using a selection of applications from business, management and finance. The text includes accessible treatment of all the ideas and concepts relevant to students in these areas of study.
This book is written for MBA students and statistics teachers of Anna University affiliated institutions. It is a natural outcome of the author, after teaching statistics several times for MBA students. It is shaped and reshaped several times to heal the heart and soul of non-mathematical community. This book covers all models in all chapters, completely. Problem identification is the most difficult task in statistics for the students. Hence a new approach with short cuts is used throughout the book to simplify this task. This book differs from other books in approaching the sampling distribution. Sampling distribution chapter is usually classified based on standard error, confidence interval estimation and hypothesis testing; or based on the number of sample sets – one sample, two sample; or based on the sample size – large sample, small sample; or based on the statistical tables – such as z test, t test, chi square test and F test. But this book classifies the sampling distribution chapter based on the parameters – Mean, Proportion, Standard deviation cum Variance. Because the very first thing to be decided by any researcher or a practitioner or a decision maker before applying any statistical tool is the parameter to be used and none other! The syllabus is reorganized as per the convenience of the students. 2nd and 3rd unit of the syllabus is reorganized based on the parameters – Mean, Proportion and Standard deviation instead of standard error, interval estimation and hypothesis testing. Similarly the discrete distributions – binomial & Poisson distributions and Probability rules of 1st unit are dealt at the end. Probability rules are grouped based on two models – associated events and successive events. Each Chapter contains illustrations, examples, formula, short answers and exercise.