Elementary Statistics
Author | : William Cyrus Navidi |
Publisher | : |
Total Pages | : |
Release | : 2013 |
Genre | : Mathematical statistics |
ISBN | : 9780077440619 |
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Author | : William Cyrus Navidi |
Publisher | : |
Total Pages | : |
Release | : 2013 |
Genre | : Mathematical statistics |
ISBN | : 9780077440619 |
Author | : Philip Rowe |
Publisher | : John Wiley & Sons |
Total Pages | : 431 |
Release | : 2015-07-20 |
Genre | : Medical |
ISBN | : 1118913418 |
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.
Author | : Gary Smith |
Publisher | : Academic Press |
Total Pages | : 397 |
Release | : 2015-06-08 |
Genre | : Mathematics |
ISBN | : 0128034920 |
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
Author | : David Moore |
Publisher | : W H Freeman & Company |
Total Pages | : 497 |
Release | : 2011-04-15 |
Genre | : Mathematics |
ISBN | : 9781429298674 |
Author | : D.G. Rees |
Publisher | : CRC Press |
Total Pages | : 384 |
Release | : 2018-10-03 |
Genre | : Mathematics |
ISBN | : 1482295687 |
An introductory text for students taking a first course in statistics-in fields as diverse as engineering, business, chemistry, and biology-Essential Statistics: Fourth Edition thoroughly updates and enhances the hugely successful third edition. It presents new information on modern statistical techniques such as Analysis of Variance (ANOVA), and software such as MINITABTM for WINDOWS. An experienced former lecturer, the author communicates to students in his trademark easy-to-follow style. Keeping complex mathematical theory to a minimum, Rees presents a wealth of fully explained worked examples throughout the text. In addition, the end-of-chapter Worksheets relate to a variety of fields-enabling students to see the relevance of the numerous methods to their study areas. Essential Statistics: Fourth Edition emphasizes the principles and assumptions underlying the statistical methods, thus providing the tools needed for students to use and interpret statistical data effectively.
Author | : Evan Berman |
Publisher | : CQ Press |
Total Pages | : 185 |
Release | : 2016-12-30 |
Genre | : Political Science |
ISBN | : 1506348971 |
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.
Author | : Peter Bruce |
Publisher | : "O'Reilly Media, Inc." |
Total Pages | : 395 |
Release | : 2017-05-10 |
Genre | : Computers |
ISBN | : 1491952911 |
Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data
Author | : Robert N. Gould |
Publisher | : Pearson Higher Ed |
Total Pages | : 586 |
Release | : 2016-11-14 |
Genre | : Mathematics |
ISBN | : 1292161280 |
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.
Author | : J. Philip Miller |
Publisher | : Elsevier |
Total Pages | : 363 |
Release | : 2010-11-08 |
Genre | : Mathematics |
ISBN | : 0444537384 |
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
Author | : Rongpeng Li |
Publisher | : Packt Publishing Ltd |
Total Pages | : 393 |
Release | : 2020-11-12 |
Genre | : Computers |
ISBN | : 1838987568 |
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.