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Essential Statistics, Regression, and Econometrics, Second Edition, is innovative in its focus on preparing students for regression/econometrics, and in its extended emphasis on statistical reasoning, real data, pitfalls in data analysis, and modeling issues. This book is uncommonly approachable and easy to use, with extensive word problems that emphasize intuition and understanding. Too many students mistakenly believe that statistics courses are too abstract, mathematical, and tedious to be useful or interesting. To demonstrate the power, elegance, and even beauty of statistical reasoning, this book provides hundreds of new and updated interesting and relevant examples, and discusses not only the uses but also the abuses of statistics. The examples are drawn from many areas to show that statistical reasoning is not an irrelevant abstraction, but an important part of everyday life. - Includes hundreds of updated and new, real-world examples to engage students in the meaning and impact of statistics - Focuses on essential information to enable students to develop their own statistical reasoning - Ideal for one-quarter or one-semester courses taught in economics, business, finance, politics, sociology, and psychology departments, as well as in law and medical schools - Accompanied by an ancillary website with an instructors solutions manual, student solutions manual and supplementing chapters
Essential Statistics for the Pharmaceutical Sciences is targeted at all those involved in research in pharmacology, pharmacy or other areas of pharmaceutical science; everybody from undergraduate project students to experienced researchers should find the material they need. This book will guide all those who are not specialist statisticians in using sound statistical principles throughout the whole journey of a research project - designing the work, selecting appropriate statistical methodology and correctly interpreting the results. It deliberately avoids detailed calculation methodology. Its key features are friendliness and clarity. All methods are illustrated with realistic examples from within pharmaceutical science. This edition now includes expanded coverage of some of the topics included in the first edition and adds some new topics relevant to pharmaceutical research. a clear, accessible introduction to the key statistical techniques used within the pharmaceutical sciences all examples set in relevant pharmaceutical contexts. key points emphasised in summary boxes and warnings of potential abuses in ‘pirate boxes’. supplementary material - full data sets and detailed instructions for carrying out analyses using packages such as SPSS or Minitab – provided at: https://www.wiley.com/go/rowe/statspharmascience2e An invaluable introduction to statistics for any science student and an essential text for all those involved in pharmaceutical research at whatever level.
Exploring the World through Data We live in a data-driven world, and the goal of this text is to teach students how to access and analyse these data critically. Authors Rob Gould, Colleen Ryan, and Rebecca Wong want students to develop a "data habit of mind" because learning statistics is an essential life skill that extends beyond the classroom. Regardless of their math backgrounds, students will learn how to think about data and how to reason using data. With a clear, unintimidating writing style and carefully chosen pedagogy, this text makes data analysis accessible to all students. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed.
Through the use of critical thinking questions and data-based exercises Exercising Essential Statistics helps students apply the techniques described in Essential Statistics for Public Managers and Policy Analysts, Fourth Edition. This accompanying workbook gives students the opportunity to practice these techniques through hands-on, carefully crafted exercises. Various examples are provided from human resource management, organizational behavior, budgeting, and public policy to illustrate how public administrators interact with and analyze data.
Reinforce your understanding of data science and data analysis from a statistical perspective to extract meaningful insights from your data using Python programming Key FeaturesWork your way through the entire data analysis pipeline with statistics concerns in mind to make reasonable decisionsUnderstand how various data science algorithms functionBuild a solid foundation in statistics for data science and machine learning using Python-based examplesBook Description Statistics remain the backbone of modern analysis tasks, helping you to interpret the results produced by data science pipelines. This book is a detailed guide covering the math and various statistical methods required for undertaking data science tasks. The book starts by showing you how to preprocess data and inspect distributions and correlations from a statistical perspective. You’ll then get to grips with the fundamentals of statistical analysis and apply its concepts to real-world datasets. As you advance, you’ll find out how statistical concepts emerge from different stages of data science pipelines, understand the summary of datasets in the language of statistics, and use it to build a solid foundation for robust data products such as explanatory models and predictive models. Once you’ve uncovered the working mechanism of data science algorithms, you’ll cover essential concepts for efficient data collection, cleaning, mining, visualization, and analysis. Finally, you’ll implement statistical methods in key machine learning tasks such as classification, regression, tree-based methods, and ensemble learning. By the end of this Essential Statistics for Non-STEM Data Analysts book, you’ll have learned how to build and present a self-contained, statistics-backed data product to meet your business goals. What you will learnFind out how to grab and load data into an analysis environmentPerform descriptive analysis to extract meaningful summaries from dataDiscover probability, parameter estimation, hypothesis tests, and experiment design best practicesGet to grips with resampling and bootstrapping in PythonDelve into statistical tests with variance analysis, time series analysis, and A/B test examplesUnderstand the statistics behind popular machine learning algorithmsAnswer questions on statistics for data scientist interviewsWho this book is for This book is an entry-level guide for data science enthusiasts, data analysts, and anyone starting out in the field of data science and looking to learn the essential statistical concepts with the help of simple explanations and examples. If you’re a developer or student with a non-mathematical background, you’ll find this book useful. Working knowledge of the Python programming language is required.
Dive into the most common statistical tests and software packages used for scientific data analysis and interpretation In Essential Statistics For Bioscientists, experienced university and bioscientist Dr Mohammed Meah delivers easy access to statistical analysis and data presentation. It is a great resource for students in the field of life and health sciences to conceptualize, analyze, and present data. This book uses three popular and commonly used statistics softwares—Microsoft Excel, Graphpad Prism, and SPSS—and offers clear, step-by-step instructions for essential data analysis and graphical/tabular display of data. Beginning with fundamental statistics terminology and concepts, including data types, descriptive statistics (central and spread of data), exploratory statistics (graphical display) and inferential statistics (hypothesis testing and correlation), the content gradually builds in complexity, explaining which statistical test is best suited and how to perform it. A thorough introduction to basic statistical terms and building up to an advanced level of statistical application- ideal for those new to study of statistics Extensive application of three popular software packages- Microsoft Excel, Graphpad Prism and SPSS Numerous hands-on examples of performing data analysis using Microsoft Excel, Graphpad Prism, and SPSS Considers the limitations and errors of statistical analysis Essential reading for those designing and planning a research project in Biosciences Perfect for undergraduate students in the life and health sciences, Essential Statistics For Bioscientists will also earn a place in the libraries of anyone studying medicine, nursing, physiotherapy, pharmacy, and dentistry requiring a refresher or primer on statistical fundamentals.
Essentials of Statistics for the Behavioral Sciences is a concise version of Statistics for the Behavioral Sciences by award-winning teacher, author, and advisor Gregory J. Privitera. The Second Edition provides balanced coverage for today’s students, connecting the relevance of core concepts to daily life with new introductory vignettes for every chapter, while speaking to the reader as a researcher when covering statistical theory, computation, and application. Robust pedagogy allows students to continually check their comprehension and hone their skills while working through carefully developed problems and exercises that include current research and seamless integration of IBM® SPSS® Statistics. Readers will welcome Privitera’s thoughtful instruction, conversational voice, and application of statistics to real-world problems. A Complete Teaching & Learning Package . SAGE coursepacks FREE! SAGE coursepacks makes it easy to import our quality instructor and student resource content into your school’s learning management system (LMS). Intuitive and simple to use, SAGE coursepacks allows you to customize course content to meet your students’ needs. . SAGE edge FREE! SAGE edge offers both instructors and students a robust online environment with an impressive array of teaching and learning resources. Study Guide With IBM® SPSS® Workbook Bundle the Second Edition with the accompanying Student Study Guide With IBM® SPSS® Workbook for Essential Statistics for the Behavioral Sciences. Guide for Users of R, SAS®, and Stata® Bundle the Second Edition with the accompanying Essentials of Statistical Analysis "In Focus". WebAssign® This title is available on WebAssign, allowing instructors to produce and manage assignments with their students online using a grade book that allows them to track and monitor students′ progress. Students receive unlimited practice using a combination of multiple choice and algorithmic questions, and are allowed unlimited access to this edition of the textbook in the same course at no additional cost. WebAssign provides instant feedback and links directly to the accompanying eBook section where the concept was covered, allowing students to find the correct solution.
Essential Statistical Methods for Medical Statistics presents only key contributions which have been selected from the volume in the Handbook of Statistics: Medical Statistics, Volume 27 (2009). While the use of statistics in these fields has a long and rich history, the explosive growth of science in general, and of clinical and epidemiological sciences in particular, has led to the development of new methods and innovative adaptations of standard methods. This volume is appropriately focused for individuals working in these fields. Contributors are internationally renowned experts in their respective areas. - Contributors are internationally renowned experts in their respective areas - Addresses emerging statistical challenges in epidemiological, biomedical, and pharmaceutical research - Methods for assessing Biomarkers, analysis of competing risks - Clinical trials including sequential and group sequential, crossover designs, cluster randomized, and adaptive designs - Structural equations modelling and longitudinal data analysis