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Author: Mohammed Meah
Publisher: John Wiley & Sons
ISBN: 1119712009
Category : Medical
Languages : en
Pages : 260
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Book Description
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.
Author: Mohammed Meah
Publisher: John Wiley & Sons
ISBN: 1119712009
Category : Medical
Languages : en
Pages : 260
Get Book Here
Book Description
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.
Author: Mohammed Meah
Publisher: John Wiley & Sons
ISBN: 1119712025
Category : Medical
Languages : en
Pages : 260
Get Book Here
Book Description
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.
Author: C. Mack
Publisher: Springer Science & Business Media
ISBN: 1461586151
Category : Computers
Languages : en
Pages : 180
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Book Description
Statistics is of ever-increasing importance in Science and Technology and this book presents the essentials of the subject in a form suitable either as the basis of a course of lectures or to be read and/or used on its own. It assumes very little in the way of mathematical knowledge-just the ability to substitute numerically in a few simple formulae. However, some mathematical proofs are outlined or given in full to illustrate the derivation of the subject; these can be omitted without loss of understanding. The book does aim at making clear the scope and nature of those essential tests and methods that a scientist or technologist is likely to need; to this end each chapter has been divided into sections with their own subheadings and some effort has been made to make the text unambiguous (if any reader finds a misleading point anywhere I hope he will write to me about it). Also with this aim in view, the equality of probability to proportion of population is stated early, then the normal distribution and the taking of samples is discussed. This occupies the first five chapters. With the principles of these chapters understood, the student can immediately learn the significance tests of Chapter 6 and, if he needs it, the analysis of variance of Chapter 7. For some scientists this will be most of what they need. However, they will be in a position to read and/or use the remaining chapters without undue difficulty.
Author: Peter Bruce
Publisher: "O'Reilly Media, Inc."
ISBN: 1491952911
Category : Computers
Languages : en
Pages : 322
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Book Description
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: Dawn Hawkins
Publisher: Oxford University Press, USA
ISBN: 0199650446
Category : Mathematics
Languages : en
Pages : 363
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Book Description
Offering a student-focused introduction to the use of statistics in the study of the biosciences, this text looks at statistical techniques and other essential tools for bioscientists, giving students the confidence to use and further explore the key techniques for themselves.
Author: Alan Agresti
Publisher: CRC Press
ISBN: 1000462919
Category : Business & Economics
Languages : en
Pages : 486
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Book Description
Foundations of Statistics for Data Scientists: With R and Python is designed as a textbook for a one- or two-term introduction to mathematical statistics for students training to become data scientists. It is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modeling. The book assumes knowledge of basic calculus, so the presentation can focus on "why it works" as well as "how to do it." Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python. The book also introduces modern topics that do not normally appear in mathematical statistics texts but are highly relevant for data scientists, such as Bayesian inference, generalized linear models for non-normal responses (e.g., logistic regression and Poisson loglinear models), and regularized model fitting. The nearly 500 exercises are grouped into "Data Analysis and Applications" and "Methods and Concepts." Appendices introduce R and Python and contain solutions for odd-numbered exercises. The book's website has expanded R, Python, and Matlab appendices and all data sets from the examples and exercises.
Author: Stephen Ashcroft
Publisher: Palgrave
ISBN: 9780333960448
Category : Mathematics
Languages : en
Pages : 168
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Book Description
Practical Statistics for the Biological Sciences is a handbook of statistical methods for use by workers in the biological sciences at all levels from undergraduate to post-doctoral researcher. The book presents, in a clear and compact form, the most common statistical tests used in the biosciences. It provides a series of flow charts to help in selecting the appropriate test. Each test is described concisely and illustrated by worked examples. The text is accompanied by a CD-ROM containing both Windows and Apple Macintosh versions of PractiStat, a new programme for statistical analysis. PractiStat can be used both as a teaching aid to work through the examples provided and as a valuable, easy to use tool for analysis of the users' own data. The programme provides a simple, intuitive interface and permits the application of the common statistical tests and procedures used by bioscientists.
Author: Dawn May Hawkins
Publisher: Oxford University Press, USA
ISBN:
Category : Medical
Languages : en
Pages : 320
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Book Description
Offering a student-focused introduction to the use of statistics in the study of the biosciences, this text looks at statistical techniques and other essential tools for bioscientists, giving students the confidence to use and further explore the key techniques for themselves.
Author: Harald B. Teicher
Publisher: Labcoat Guide to Crop Protecti
ISBN: 9781798120903
Category : Science
Languages : en
Pages : 184
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Book Description
Are you a student, researcher or science leader looking for an overview of the essential principles of Biostatistics? This book is an easily accessible primer for scientists and research workers not trained in mathematical theory, but who have previously followed a course in Biological Statistics. This book provides a readily accessible overview on how to plan, implement and analyse experiments without access to a dedicated staff of statisticians. Guide To Essential Biostatistics contains few calculations (the "how" of Biostatistics) but instead provides a plain-English overview of the "why" - what is it the numbers are telling us, and how can we use this to plan trials, understand our data and make decisions. Designed to fit in a lab coat pocket for easy access, this GUIDE TO ESSENTIAL BIOSTATISTICS compiles some of the most-used biostatistical techniques, approximations and rules-of-thumb used in the design and analysis of biological experiments. The author has a 20+ year R&D background in the Corporate & Academic AgChem & BioScience community, and provides strategic and technical expertise to start-ups and corporations developing chemical and biological crop protection products. Buy this book to obtain an overview of essential aspects of Biostatistics! By purchasing the print edition of this book on AMAZON, you are eligible for a FREE download of the eBook version, providing access to high-resolution, zoomable color images.
Author: Richard Boddy
Publisher: John Wiley & Sons
ISBN: 0470746645
Category : Mathematics
Languages : en
Pages : 249
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Book Description
This is a practical book on how to apply statistical methods successfully. The Authors have deliberately kept formulae to a minimum to enable the reader to concentrate on how to use the methods and to understand what the methods are for. Each method is introduced and used in a real situation from industry or research. Each chapter features situations based on the authors’ experience and looks at statistical methods for analysing data and, where appropriate, discusses the assumptions of these methods. Key features: Provides a practical hands-on manual for workplace applications. Introduces a broad range of statistical methods from confidence intervals to trend analysis. Combines realistic case studies and examples with a practical approach to statistical analysis. Features examples drawn from a wide range of industries including chemicals, petrochemicals, nuclear power, food and pharmaceuticals. Includes a supporting website, providing software to aid tutorials. Scientists and technologists of all levels who are required to design, conduct and analyse experiments will find this book to be essential reading.
