Understanding and Using Advanced Statistics PDF Download
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Author: Jeremy J Foster
Publisher: SAGE
ISBN: 9781412900140
Category : Mathematics
Languages : en
Pages : 196
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Book Description
Understanding and Using Advanced Statistics is a comprehensive, practical guide for postgraduate students advising how and when to use more advanced statistical methods. Perfect for students without a mathematical background, the authors refresh important basics such as descriptive statistics and research design as well as introducing essential upper-level techniques to cater for the advanced student. Key Features: - Comprehensive guide informing how to use a range of advanced statistical methods such as MANOVA, path analysis and logistical regression; - Inter-disciplinary: ideal for students studying upper level statistical methods in any subject across the social sciences; - Practical guide: case studies, further reading, key terms explained in order to help the non-mathematically orientated student get ahead with their research. Building on undergraduate statistical grounding, Understanding and Using Advanced Statistics provides the upper-level researcher with the knowledge of what advanced statistics do, how they should be used, and what their output means.
Author: Jeremy J Foster
Publisher: SAGE
ISBN: 9781412900140
Category : Mathematics
Languages : en
Pages : 196
Get Book
Book Description
Understanding and Using Advanced Statistics is a comprehensive, practical guide for postgraduate students advising how and when to use more advanced statistical methods. Perfect for students without a mathematical background, the authors refresh important basics such as descriptive statistics and research design as well as introducing essential upper-level techniques to cater for the advanced student. Key Features: - Comprehensive guide informing how to use a range of advanced statistical methods such as MANOVA, path analysis and logistical regression; - Inter-disciplinary: ideal for students studying upper level statistical methods in any subject across the social sciences; - Practical guide: case studies, further reading, key terms explained in order to help the non-mathematically orientated student get ahead with their research. Building on undergraduate statistical grounding, Understanding and Using Advanced Statistics provides the upper-level researcher with the knowledge of what advanced statistics do, how they should be used, and what their output means.
Author: Peter Westfall
Publisher: CRC Press
ISBN: 1466512105
Category : Mathematics
Languages : en
Pages : 572
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Book Description
Providing a much-needed bridge between elementary statistics courses and advanced research methods courses, Understanding Advanced Statistical Methods helps students grasp the fundamental assumptions and machinery behind sophisticated statistical topics, such as logistic regression, maximum likelihood, bootstrapping, nonparametrics, and Bayesian methods. The book teaches students how to properly model, think critically, and design their own studies to avoid common errors. It leads them to think differently not only about math and statistics but also about general research and the scientific method. With a focus on statistical models as producers of data, the book enables students to more easily understand the machinery of advanced statistics. It also downplays the "population" interpretation of statistical models and presents Bayesian methods before frequentist ones. Requiring no prior calculus experience, the text employs a "just-in-time" approach that introduces mathematical topics, including calculus, where needed. Formulas throughout the text are used to explain why calculus and probability are essential in statistical modeling. The authors also intuitively explain the theory and logic behind real data analysis, incorporating a range of application examples from the social, economic, biological, medical, physical, and engineering sciences. Enabling your students to answer the why behind statistical methods, this text teaches them how to successfully draw conclusions when the premises are flawed. It empowers them to use advanced statistical methods with confidence and develop their own statistical recipes. Ancillary materials are available on the book’s website.
Author: Jeremy J Foster
Publisher: SAGE
ISBN: 9781412900140
Category : Social Science
Languages : en
Pages : 196
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Book Description
The spread of sophisticated computer packages and the machinery on which to run them has meant that procedures which were previously only available to experienced researchers with access to expensive machines and research students can now be carried out in a few seconds by almost every undergraduate. Understanding and Using Advanced Statistics provides the basis for gaining an understanding of what these analytic procedures do, when they should be used, and what the results provided signify. This comprehensive textbook guides students and researchers through the transition from simple statistics to more complex procedures with accessible language and illustration.
Author: Larry Hatcher
Publisher: Shadow Finch Media LLC
ISBN: 9780985867003
Category : Mathematical statistics
Languages : en
Pages : 632
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Book Description
"Advanced Statistics in Research: Reading, Understanding, and Writing Up Data Analysis Results" is the simple, nontechnical introduction to the most complex multivariate statistics presented in empirical research articles. "wwwStatsInResearch.com, " is a companion website that provides free sample chapters, exercises, and PowerPoint slides for students and teachers. A free 600-item test bank is available to instructors. "Advanced Statistics in Research" does not show how to "perform" statistical procedures--it shows how to read, understand, and interpret them, as they are typically presented in journal articles and research reports. It demystifies the sophisticated statistics that stop most readers cold: multiple regression, logistic regression, discriminant analysis, ANOVA, ANCOVA, MANOVA, factor analysis, path analysis, structural equation modeling, meta-analysis--and more. "Advanced Statistics in Research" assumes that you have never had a course in statistics. It begins at the beginning, with research design, central tendency, variability, z scores, and the normal curve. You will learn (or re-learn) the big-three results that are common to most procedures: statistical significance, confidence intervals, and effect size. Step-by-step, each chapter gently builds on earlier concepts. Matrix algebra is avoided, and complex topics are explained using simple, easy-to-understand examples. "Need help writing up your results?" Advanced Statistics in Research shows how data-analysis results can be summarized in text, tables, and figures according to APA format. You will see how to present the basics (e.g., means and standard deviations) as well as the advanced (e.g., factor patterns, post-hoc tests, path models, and more). "Advanced Statistics in Research" is appropriate as a textbook for graduate students and upper-level undergraduates (see supplementary materials at StatsInResearch.com). It also serves as a handy shelf reference for investigators and all consumers of research.
Author: Thomas Baguley
Publisher: Bloomsbury Publishing
ISBN: 0230363555
Category : Psychology
Languages : en
Pages : 864
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Book Description
Ideal for experienced students and researchers in the social sciences who wish to refresh or extend their understanding of statistics, and to apply advanced statistical procedures using SPSS or R. Key theory is reviewed and illustrated with examples of how to apply these concepts using real data.
Author: Liwen Vaughan
Publisher: Information Today, Inc.
ISBN: 9781573871105
Category : Business & Economics
Languages : en
Pages : 248
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Book Description
For most of us, "painless" is not the word that comes to mind when we think of statistics, but author and educator Liwen Vaughan wants to change that. In this unique and useful book, Vaughan clearly explains the statistical methods used in information science research, focusing on basic logic rather than mathematical intricacies. Her emphasis is on the meaning of statistics, when and how to apply them, and how to interpret the results of statistical analysis. Through the use of real-world examples, she shows how statistics can be used to improve services, make better decisions, and conduct more effective research. Whether you are doing statistical analysis or simply need to better understand the statistics you encounter in professional literature and the media, this book will be a valuable addition to your personal toolkit. Includes more than 80 helpful figures and tables, 7 appendices, bibliography, index.
Author: Bruce J. Chalmer
Publisher: CRC Press
ISBN: 1000715523
Category : Mathematics
Languages : en
Pages : 449
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Book Description
Introducing undergraduates to the vital concepts of statistics, this superb textbook allows instructors to include as much—or as little—mathematical detail as may be suitable for their students. Featuring Statpal statistical software for the IBM PC®, the book contains study questions that help solidify students’ understanding of the material and prepare them for the next group of concepts. Many of the exercises, labeled “Statpal exercises,” are especially written for the Statpal statistical package. Understanding Statistics begins with the basic concepts of statistical inference ... presents normal and binomial distributions, general techniques of interval estimation and hypothesis testing, and applications of these techniques to inferences about a single population mean and proportions ... and covers inferences about group differences, including parametric and nonparametric approaches to the two-group case, and the one-way ANOVA and its nonparametric analogue. In addition, this volume considers relationships between two variables, including the correlation co-efficient, Spearman’s rho, and Kendall’s tau ... surveys basic regression methods, including simple, multiple, and stepwise ... and discusses the analysis of variance of factorial designs, the concept of interaction, and the analysis of categorical data using the chi-square test. Complete with tables and drawings plus appendices that furnish instructions for using Statpal software, information on advanced topics, and much more, Understanding Statistics is an ideal text for undergraduate survey courses on statistical methods as well as for courses in economics, psychology, sociology, education, business administration, and others that require basic statistics.
Author: Larry Stephens
Publisher: McGraw Hill Professional
ISBN: 0071471014
Category : Technology & Engineering
Languages : en
Pages : 324
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Book Description
TAKE THE "MEAN" OUT OF ADVANCED STATISTICS Now anyone who has mastered basic statistics can easily take the next step up. In Advanced Statistics Demystified, experienced statistics instructor Larry J. Stephens provides an effective, anxiety-soothing, and totally painless way to learn advanced statistics -- from inferential statistics, variance analysis, and parametric and nonparametric testing to simple linear regression, correlation, and multiple regression. With Advanced Statistics Demystified, you master the subject one simple step at a time -- at your own speed. This unique self-teaching guide offers exercises at the end of each chapter to pinpoint weaknesses and two 50-question "final exams" to reinforce the entire book. If you want to build or refresh your understanding of advanced statistics, here's a fast and entertaining self-teaching course that's specially designed to reduce anxiety. Get ready to: Draw inferences by comparing means, percents, and variances from two different samples Compare more than two means with variance analysis Make accurate interpretations with simple linear regression and correlation Derive inferences, estimations, and predictions with multiple regression models Apply nonparametric tests when the assumptions for the parametric tests are not satisfied Take two "final exams" and grade them yourself! Simple enough for beginners but challenging enough for advanced students, Advanced Statistics Demystified is your direct route to confident, sophisticated statistical analysis!
Author: Himanshu Singh
Publisher: BPB Publications
ISBN: 9388511972
Category : Computers
Languages : en
Pages : 269
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Book Description
A practical guide that will help you understand the Statistical Foundations of any Machine Learning Problem Ê KEY FEATURESÊ _ Develop a Conceptual and Mathematical understanding of Statistics _ Get an overview of Statistical Applications in Python _ Learn how to perform Hypothesis testing in Statistics _ Understand why Statistics is important in Machine Learning _ Learn how to process data in Python Ê DESCRIPTIONÊÊ This book talks about Statistical concepts in detail, with its applications in Python. The book starts with an introduction to Statistics and moves on to cover some basic Descriptive Statistics concepts such as mean, median, mode, etc.Ê You will then explore the concept of Probability and look at different types of Probability Distributions. Next, you will look at parameter estimations for the unknown parameters present in the population and look at Random Variables in detail, which are used to save the results of an experiment in Statistics. You will then explore one of the most important fields in Statistics - Hypothesis Testing, and then explore various types of tests used to check our hypothesis. The last part of our book will focus on how you can process data using Python, some elements of Non-parametric statistics, and finally, some introduction to Machine Learning. Ê WHAT YOU WILLÊ LEARNÊÊ _ Understand the basics of Statistics _ Get to know more about Descriptive Statistics _ Understand and learn advanced Statistics techniques _ Learn how to apply Statistical concepts in Python _ Understand important Python packages for Statistics and Machine Learning Ê WHO THIS BOOK IS FORÊ This book is for anyone who wants to understand Statistics and its use in Machine Learning. This book will help you understand the Mathematics behind the Statistical concepts and the applications using the Python language. Having a working knowledge of the Python language is a prerequisite. TABLE OF CONTENTSÊ 1. Introduction to Statistics 2. Descriptive Statistics 3. Probability 4. Random Variables 5. Parameter Estimations 6. Hypothesis Testing 7. Analysis of Variance 8. Regression 9. Non Parametric Statistics 10. Data Analysis using Python 11. Introduction to Machine Learning
Author: Basavarajaiah D. M.
Publisher: Springer Nature
ISBN: 9811582106
Category : Medical
Languages : en
Pages : 380
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Book Description
Recent Statistical techniques are one of the basal evidence for clinical research, a pivotal in handling new clinical research and in evaluating and applying prior research. This book explores various choices of statistical tools and mechanisms, analyses of the associations among different clinical attributes. It uses advanced statistical methods to describe real clinical data sets, when the clinical processes being examined are still in the process. This book also discusses distinct methods for building predictive and probability distribution models in clinical situations and ways to assess the stability of these models and other quantitative conclusions drawn by realistic experimental data sets. Design of experiments and recent posthoc tests have been used in comparing treatment effects and precision of the experimentation. This book also facilitates clinicians towards understanding statistics and enabling them to follow and evaluate the real empirical studies (formulation of randomized control trial) that pledge insight evidence base for clinical practices. This book will be a useful resource for clinicians, postgraduates scholars in medicines, clinical research beginners and academicians to nurture high-level statistical tools with extensive scope.
