Fundamentals of Descriptive Statistics

Author: Zealure C Holcomb
Publisher: Routledge
ISBN: 1351970321
Format: PDF
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• Do your students need to organize and summarize data for term projects? Will they need to perform these tasks on the job? This book gives them thorough preparation. • In twelve short chapters, your students will learn the purposes of descriptive statistics, their calculation, and proper interpretation. • Actual data on the emotional health of foster-care adolescents are used throughout the book to illustrate various ways of deriving meaning from the data with descriptive statistics. Other interesting examples are also included. • Computational procedures are illustrated with step-by-step, easy-to-follow examples. • End-of-chapter exercises provide ample practice for students to master both computations and statistical concepts. • Eliminates the need for students to buy a traditional statistics book that emphasizes inferential statistics. • Thoroughly field-tested for student comprehension. • The answer key makes it easy for you to start using this book right away. • This book will please you and your students with its clarity of presentation. • Outstanding supplement for students who need to describe term project data.

Fundamentals of Descriptive Statistics

Author: Zealure C. Holcomb
Publisher: Pyrczak Publishing
ISBN:
Format: PDF, ePub
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Your students will learn the purposes of descriptive statistics, their calculation, and proper interpretation with this concise book. Actual data is used to illustrate various ways of deriving meaning from data with descriptive statistics. This book has been thoroughly field tested for student comprehension.

Introduction to Statistics

Author: Howard M. Reid
Publisher: SAGE Publications
ISBN: 1483324281
Format: PDF, ePub, Docs
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Using a truly accessible and reader-friendly approach, Introduction to Statistics: Fundamental Concepts and Procedures of Data Analysis, by Howard M. Reid, redefines the way statistics can be taught and learned. Unlike other books that merely focus on procedures, Reid’s approach balances development of critical thinking skills with application of those skills to contemporary statistical analysis. He goes beyond simply presenting techniques by focusing on the key concepts readers need to master in order to ensure their long-term success. Indeed, this exciting new book offers the perfect foundation upon which readers can build as their studies and careers progress to more advanced forms of statistics. Keeping computational challenges to a minimum, Reid shows readers not only how to conduct a variety of commonly used statistical procedures, but also when each procedure should be utilized and how they are related. Following a review of descriptive statistics, he begins his discussion of inferential statistics with a two-chapter examination of the Chi Square test to introduce students to hypothesis testing, the importance of determining effect size, and the need for post hoc tests. When more complex procedures related to interval/ratio data are covered, students already have a solid understanding of the foundational concepts involved. Exploring challenging topics in an engaging and easy-to-follow manner, Reid builds concepts logically and supports learning through robust pedagogical tools, the use of SPSS, numerous examples, historical quotations, insightful questions, and helpful progress checks.

Business Statistics Made Easy in SAS

Author: Gregory Lee
Publisher: SAS Institute
ISBN: 162960044X
Format: PDF, Kindle
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Learn or refresh core statistical methods for business with SAS® and approach real business analytics issues and techniques using a practical approach that avoids complex mathematics and instead employs easy-to-follow explanations. Business Statistics Made Easy in SAS® is designed as a user-friendly, practice-oriented, introductory text to teach businesspeople, students, and others core statistical concepts and applications. It begins with absolute core principles and takes you through an overview of statistics, data and data collection, an introduction to SAS®, and basic statistics (descriptive statistics and basic associational statistics). The book also provides an overview of statistical modeling, effect size, statistical significance and power testing, basics of linear regression, introduction to comparison of means, basics of chi-square tests for categories, extrapolating statistics to business outcomes, and some topical issues in statistics, such as big data, simulation, machine learning, and data warehousing. The book steers away from complex mathematical-based explanations, and it also avoids basing explanations on the traditional build-up of distributions, probability theory and the like, which tend to lose the practice-oriented reader. Instead, it teaches the core ideas of statistics through methods such as careful, intuitive written explanations, easy-to-follow diagrams, step-by-step technique implementation, and interesting metaphors. With no previous SAS experience necessary, Business Statistics Made Easy in SAS® is an ideal introduction for beginners. It is suitable for introductory undergraduate classes, postgraduate courses such as MBA refresher classes, and for the business practitioner. It is compatible with SAS® University Edition.

Linear Statistical Inference and its Applications

Author: C. Radhakrishna Rao
Publisher: John Wiley & Sons
ISBN: 0470317140
Format: PDF
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"C. R. Rao would be found in almost any statistician's list of five outstanding workers in the world of Mathematical Statistics today. His book represents a comprehensive account of the main body of results that comprise modern statistical theory." -W. G. Cochran "[C. R. Rao is] one of the pioneers who laid the foundations of statistics which grew from ad hoc origins into a firmly grounded mathematical science." -B. Efrom Translated into six major languages of the world, C. R. Rao's Linear Statistical Inference and Its Applications is one of the foremost works in statistical inference in the literature. Incorporating the important developments in the subject that have taken place in the last three decades, this paperback reprint of his classic work on statistical inference remains highly applicable to statistical analysis. Presenting the theory and techniques of statistical inference in a logically integrated and practical form, it covers: * The algebra of vectors and matrices * Probability theory, tools, and techniques * Continuous probability models * The theory of least squares and the analysis of variance * Criteria and methods of estimation * Large sample theory and methods * The theory of statistical inference * Multivariate normal distribution Written for the student and professional with a basic knowledge of statistics, this practical paperback edition gives this industry standard new life as a key resource for practicing statisticians and statisticians-in-training.

Fundamentals of Quality Control and Improvement

Author: Amitava Mitra
Publisher: John Wiley & Sons
ISBN: 1118705440
Format: PDF
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A statistical approach to the principles of quality control and management Incorporating modern ideas, methods, and philosophies of quality management, Fundamentals of Quality Control and Improvement, Fourth Edition presents a quantitative approach to management-oriented techniques and enforces the integration of statistical concepts into quality assurance methods. Utilizing a sound theoretical foundation and illustrating procedural techniques through real-world examples, the timely new edition bridges the gap between statistical quality control and quality management. Promoting a unique approach, the book focuses on the use of experimental design concepts as well as the Taguchi method for creating product/process designs that successfully incorporate customer needs, improve lead time, and reduce costs. The Fourth Edition of Fundamentals of Quality Control and Improvement also includes: New topical coverage on risk-adjustment, capability indices, model building using regression, and survival analysis Updated examples and exercises that enhance the readers’ understanding of the concepts Discussions on the integration of statistical concepts to decision making in the realm of quality assurance Additional concepts, tools, techniques, and issues in the field of health care and health care quality A unique display and analysis of customer satisfaction data through surveys with strategic implications on decision making, based on the degree of satisfaction and the degree of importance of survey items Fundamentals of Quality Control and Improvement, Fourth Edition is an ideal book for undergraduate and graduate-level courses in management, technology, and engineering. The book also serves as a valuable reference for practitioners and professionals interested in expanding their knowledge of statistical quality control, quality assurance, product/process design, total quality management, and/or Six Sigma training in quality improvement.

Early Statistics Fundamentals

Author: Antonio Curtis
Publisher: Createspace Independent Publishing Platform
ISBN: 9781974008209
Format: PDF
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This text provides a different approach to a first course in Statistics. The most essential topics are explored in depth, with detailed explanations of examples. The goal is to prepare students for upper division courses in which Statistics will be used so that they walk into those courses ready to grasp the new material. Probability is discussed minimally, solely for the purpose of enabling students to use Statistics. Students with only an algebra background and no science background can absorb and benefit from this book. The entire text can realistically be thoroughly covered in a one semester or one quarter course. After learning the material in this text, students will be able to assess a research situation, understand the correct statistical method to use for that situation, and then completely understand the real world meaning of the results obtained from using the procedure. There is variety in the way problems are worded so that students do not figure out what to do based on memorizing patterns in problem structure. "Extra information" is routinely included in problems so students need to think critically. Both by-hand and computer-based problems are presented so students gain an appreciation for how the statistical methods work, and can also interpret the output of technology-based statistical analysis. Descriptive statistics and inferential statistics are considered, including one- and two-factor ANOVA as well as the chi-square tests for Goodness of Fit and Independence. At the end of confidence interval and hypothesis test chapters there is a section containing mixtures of various types of problems so students need to figure out how to handle problems without the usual context clue of similar problems being grouped together. The text contains a balance of theory and practice, with indications of how the current material leads to upper division studies. An earnest effort is made to get students excited about Statistics, not simply to pass their Statistics class.

Fundamentals of Statistics

Author: H. Mulholland
Publisher: Butterworth-Heinemann
ISBN: 1483106047
Format: PDF, Kindle
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Fundamentals of Statistics covers topics on the introduction, fundamentals, and science of statistics. The book discusses the collection, organization and representation of numerical data; elementary probability; the binomial Poisson distributions; and the measures of central tendency. The text describes measures of dispersion for measuring the spread of a distribution; continuous distributions for measuring on a continuous scale; the properties and use of normal distribution; and tests involving the normal or student's ‘t’ distributions. The use of control charts for sample means; the ranges and fraction defective; the chi-squared distribution; the F distribution; and the bivariate distributions are also considered. The book deals with the idea of mathematical expectation and its relationship with mean, variance, and covariance, as well as weighted averages, death rates, and time series. Students studying for advanced level education or higher national certificates in Mechanical or Electrical Engineering, Mathematics, Chemistry, Biology, or Pharmacy, as well as university students taking such courses will find the book invaluable.

The R Software

Author: Pierre Lafaye de Micheaux
Publisher: Springer Science & Business
ISBN: 1461490200
Format: PDF
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The contents of The R Software are presented so as to be both comprehensive and easy for the reader to use. Besides its application as a self-learning text, this book can support lectures on R at any level from beginner to advanced. This book can serve as a textbook on R for beginners as well as more advanced users, working on Windows, MacOs or Linux OSes. The first part of the book deals with the heart of the R language and its fundamental concepts, including data organization, import and export, various manipulations, documentation, plots, programming and maintenance. The last chapter in this part deals with oriented object programming as well as interfacing R with C/C++ or Fortran, and contains a section on debugging techniques. This is followed by the second part of the book, which provides detailed explanations on how to perform many standard statistical analyses, mainly in the Biostatistics field. Topics from mathematical and statistical settings that are included are matrix operations, integration, optimization, descriptive statistics, simulations, confidence intervals and hypothesis testing, simple and multiple linear regression, and analysis of variance. Each statistical chapter in the second part relies on one or more real biomedical data sets, kindly made available by the Bordeaux School of Public Health (Institut de Santé Publique, d'Épidémiologie et de Développement - ISPED) and described at the beginning of the book. Each chapter ends with an assessment section: memorandum of most important terms, followed by a section of theoretical exercises (to be done on paper), which can be used as questions for a test. Moreover, worksheets enable the reader to check his new abilities in R. Solutions to all exercises and worksheets are included in this book.

Fundamental Statistical Principles for the Neurobiologist

Author: Stephen W. Scheff
Publisher: Academic Press
ISBN: 0128050519
Format: PDF, ePub, Mobi
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Fundamental Statistical Principles for Neurobiologists introduces readers to basic experimental design and statistical thinking in a comprehensive, relevant manner. This book is an introductory statistics book that covers fundamental principles written by a neuroscientist who understands the plight of the neuroscience graduate student and the senior investigator. It summarizes the fundamental concepts associated with statistical analysis that are useful for the neuroscientist, and provides understanding of a particular test in language that is more understandable to this specific audience, with the overall purpose of explaining which statistical technique should be used in which situation. Different types of data are discussed such as how to formulate a research hypothesis, the primary types of statistical errors and statistical power, followed by how to actually graph data and what kinds of mistakes to avoid. Chapters discuss variance, standard deviation, standard error, mean, confidence intervals, correlation, regression, parametric vs. nonparametric statistical tests, ANOVA, and post hoc analyses. Finally, there is a discussion on how to deal with data points that appear to be "outliers" and what to do when there is missing data, an issue that has not sufficiently been covered in literature. An introductory guide to statistics aimed specifically at the neuroscience audience Contains numerous examples with actual data that is used in the analysis Gives the investigators a starting pointing for evaluating data in easy-to-understand language Explains in detail many different statistical tests commonly used by neuroscientists