Fundamentals of Descriptive Statistics

Author: Zealure C Holcomb
Publisher: Routledge
ISBN: 1351970321
Format: PDF, Mobi
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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
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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.

Fundamentals of Biostatistics

Author: Bernard Rosner
Publisher: Cengage Learning
ISBN: 1133008178
Format: PDF
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Bernard Rosner's FUNDAMENTALS OF BIOSTATISTICS is a practical introduction to the methods, techniques, and computation of statistics with human subjects. It prepares students for their future courses and careers by introducing the statistical methods most often used in medical literature. Rosner minimizes the amount of mathematical formulation (algebra-based) while still giving complete explanations of all the important concepts. As in previous editions, a major strength of this book is that every new concept is developed systematically through completely worked out examples from current medical research problems. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Statistics for Business Economics Revised

Author: David R. Anderson
Publisher: Cengage Learning
ISBN: 1337516716
Format: PDF
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Get more out of learning statistics than simply the ability to solve equations. Discover how statistical information enables strong decisions in today’s business world with STATISTICS FOR BUSINESS AND ECONOMICS, REVISED 13E. Sound methodology combines with a proven problem-scenario approach, and meaningful applications for the most powerful approach to mastering critical statistical concepts. This edition’s prestigious author team brings together more than 25 years of unmatched experience to this thoroughly updated book. More than 350 real business examples, timely cases, and memorable exercises present the latest statistical data and business information with unwavering accuracy. To ensure the most relevant coverage, this edition introduces how to use today’s most popular commercial statistical software programs, including Minitab 17 and Excel 2016. Trust this edition for the statistics background needed for business success. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

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.

Fundamentals of Applied Probability and Random Processes

Author: Oliver Ibe
Publisher: Academic Press
ISBN: 0128010355
Format: PDF, Mobi
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The long-awaited revision of Fundamentals of Applied Probability and Random Processes expands on the central components that made the first edition a classic. The title is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability to real-world problems, and introduce the basics of statistics. The book's clear writing style and homework problems make it ideal for the classroom or for self-study. Demonstrates concepts with more than 100 illustrations, including 2 dozen new drawings Expands readers’ understanding of disruptive statistics in a new chapter (chapter 8) Provides new chapter on Introduction to Random Processes with 14 new illustrations and tables explaining key concepts. Includes two chapters devoted to the two branches of statistics, namely descriptive statistics (chapter 8) and inferential (or inductive) statistics (chapter 9).

LSC Fundamentals of Quantitative Business Methods Business Tools and Cases in Mathematics Descriptive Statistics and Probability

Author: Mark Soskin
Publisher: McGraw-Hill/Irwin
ISBN: 9780072368246
Format: PDF, ePub
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This is the story of a breakthrough in competency-based quantitative business education. Begun in 1991 as part of a college-wide effort to revolutionize business education instruction. The foundations of the new approach were the following four competencies: Teamwork, Communication, Creative Thinking and Adapting to Change. The introductory quantitative methods course occupies a critical position in a competency-based curriculum. An effective "quant methods" course must challenge students to enlist quantitative techniques to solve business problems and establish a lifelong link between data analysis and business decision making. Like many other business programs, we formerly gave responsibility for teaching business mathematics, descriptive statistics, and probability to departments outside the business college. As elsewhere, we were deeply concerned that business math and basic stat courses were generally ill-suited to our business curriculum needs. For example, out business curriculum made little use of material from the business calculus course required in our program. We also discovered that anxiety about these quantitative courses were so high that many students postponed taking them until right before graduation. By requiring a course whose material was seldom applied, the not so subtle and erroneous message was sent to students that fundamental math, stat, and probability is not useful in business. For competency-based education to be successful, quantitative learning must be effectively linked to the rest of the curriculum. First, only quantitative tools directly useful to solving fundamental business problems were to be included in the new course. To obtain this core of tools, we surveyed our business faculty to identify critical methods and concepts most needed by students in each major business areas. Next, we designed an entirely new course around this essential core of quantitative tools. Finally, a revolutionary textbook was developed that fosters quantitative learning through the four business competencies and emphasizes these core methods and concepts. After several years of classroom trials and student feedback, Fundamentals of Quantitative Business Methods is the end result of this process. This text, now in its third edition, helps students identify how each of the four competencies relates to mathematical and statistical reasoning and business modeling techniques. Some problems and cases may also be used to develop teamwork skills through cooperative learning. By working and studying in teams, students can better assess how well they understand the material and can help each other to learn critical problem-solving skills.

Fundamentals of Quality Control and Improvement

Author: Amitava Mitra
Publisher: John Wiley & Sons
ISBN: 1118705440
Format: PDF, ePub
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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, Docs
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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.