Download or read book Statistics Without Tears written by Derek Rowntree and published by . This book was released on 1983 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Mathematical Primer for Social Statistics written by John Fox and published by SAGE. This book was released on 2009 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ideal primer for students and researchers across the social sciences who wish to master the necessary maths in order to pursue studies involving advanced statistical methods

Download or read book A Primer on Statistical Distributions written by Narayanaswamy Balakrishnan and published by John Wiley & Sons. This book was released on 2004-12-04 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed as an introduction to statistical distribution theory. * Includes a first chapter on basic notations and definitions that are essential to working with distributions. * Remaining chapters are divided into three parts: Discrete Distributions, Continuous Distributions, and Multivariate Distributions. * Exercises are incorporated throughout the text in order to enhance understanding of materials just taught.

Download or read book A Primer of Multivariate Statistics written by Richard J. Harris and published by Psychology Press. This book was released on 2001-05-01 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing upon more than 30 years of experience in working with statistics, Dr. Richard J. Harris has updated A Primer of Multivariate Statistics to provide a model of balance between how-to and why. This classic text covers multivariate techniques with a taste of latent variable approaches. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis. This edition retains its conversational writing style while focusing on classical techniques. The book gives the reader a feel for why one should consider diving into more detailed treatments of computer-modeling and latent-variable techniques, such as non-recursive path analysis, confirmatory factor analysis, and hierarchical linear modeling. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis.

Download or read book A Mathematical Primer for Social Statistics written by John Fox and published by SAGE Publications. This book was released on 2021-01-11 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Mathematical Primer for Social Statistics, Second Edition presents mathematics central to learning and understanding statistical methods beyond the introductory level: the basic "language" of matrices and linear algebra and its visual representation, vector geometry; differential and integral calculus; probability theory; common probability distributions; statistical estimation and inference, including likelihood-based and Bayesian methods. The volume concludes by applying mathematical concepts and operations to a familiar case, linear least-squares regression. The Second Edition pays more attention to visualization, including the elliptical geometry of quadratic forms and its application to statistics. It also covers some new topics, such as an introduction to Markov-Chain Monte Carlo methods, which are important in modern Bayesian statistics. A companion website includes materials that enable readers to use the R statistical computing environment to reproduce and explore computations and visualizations presented in the text. The book is an excellent companion to a "math camp" or a course designed to provide foundational mathematics needed to understand relatively advanced statistical methods.

Download or read book Causal Inference in Statistics written by Judea Pearl and published by John Wiley & Sons. This book was released on 2016-01-25 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: CAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can tease causal information from data. Causal Inference in Statistics fills that gap. Using simple examples and plain language, the book lays out how to define causal parameters; the assumptions necessary to estimate causal parameters in a variety of situations; how to express those assumptions mathematically; whether those assumptions have testable implications; how to predict the effects of interventions; and how to reason counterfactually. These are the foundational tools that any student of statistics needs to acquire in order to use statistical methods to answer causal questions of interest. This book is accessible to anyone with an interest in interpreting data, from undergraduates, professors, researchers, or to the interested layperson. Examples are drawn from a wide variety of fields, including medicine, public policy, and law; a brief introduction to probability and statistics is provided for the uninitiated; and each chapter comes with study questions to reinforce the readers understanding.

Download or read book Statistics in MATLAB written by MoonJung Cho and published by CRC Press. This book was released on 2014-12-15 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This primer provides an accessible introduction to MATLAB version 8 and its extensive functionality for statistics. Fulfilling the need for a practical user's guide, the book covers capabilities in the main MATLAB package, the Statistics Toolbox, and the student version of MATLAB, presenting examples of how MATLAB can be used to analyze data. It explains how to determine what method should be used for analysis, and includes figures, visual aids, and access to a companion website with data sets and additional examples.

Download or read book Statistical Thinking from Scratch written by M. D. Edge and published by Oxford University Press, USA. This book was released on 2019-06-13 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers across the natural and social sciences find themselves navigating tremendous amounts of new data. Making sense of this flood of information requires more than the rote application of formulaic statistical methods. The premise of Statistical Thinking from Scratch is that students who want to become confident data analysts are better served by a deep introduction to a single statistical method than by a cursory overview of many methods. In particular, this book focuses on simple linear regression-a method with close connections to the most important tools in applied statistics-using it as a detailed case study for teaching resampling-based, likelihood-based, and Bayesian approaches to statistical inference. Considering simple linear regression in depth imparts an idea of how statistical procedures are designed, a flavour for the philosophical positions one assumes when applying statistics, and tools to probe the strengths of one's statistical approach. Key to the book's novel approach is its mathematical level, which is gentler than most texts for statisticians but more rigorous than most introductory texts for non-statisticians. Statistical Thinking from Scratch is suitable for senior undergraduate and beginning graduate students, professional researchers, and practitioners seeking to improve their understanding of statistical methods across the natural and social sciences, medicine, psychology, public health, business, and other fields.

Download or read book A Primer in Data Reduction written by Andrew S. C. Ehrenberg and published by Wiley. This book was released on 2007-04-02 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise, easy to understand introduction that emphasizes the relevance of statistics to real world problems. Describes traditional statistical methods, their uses and limitations, and explains how to reduce numerical data to statistical summaries, how to interpret the results, and how to present the data clearly. Minimizes mathematics without oversimplification and illustrates theories with practical, varied examples. Statistical tables and answers to the exercises are included.

Download or read book Primer of Biostatistics Seventh Edition written by Stanton Glantz and published by McGraw Hill Professional. This book was released on 2011-12-09 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise, engagingly written introduction to understanding statistics as they apply to medicine and the life sciences CD-ROM performs 30 statistical tests Don't be afraid of biostatistics anymore! Primer of Biostatistics,7th Edition demystifies this challenging topic in an interesting and enjoyable manner that assumes no prior knowledge of the subject. Faster than you thought possible, you'll understand test selection and be able to evaluate biomedical statistics critically, knowledgeably, and confidently. With Primer of Biostatistics, you’ll start with the basics, including analysis of variance and the t test, then advance to multiple comparison testing, contingency tables, regression, and more. Illustrative examples and challenging problems, culled from the recent biomedical literature, highlight the discussions throughout and help to foster a more intuitive approach to biostatistics. The companion CD-ROM contains everything you need to run thirty statistical tests of your own data. Review questions and summaries in each chapter facilitate the learning process and help you gauge your comprehension. By combining whimsical studies of Martians and other planetary residents with actual papers from the biomedical literature, the author makes the subject fun and engaging. Coverage includes: How to summarize data How to test for differences between groups The t test How to analyze rates and proportions What does “not significant” really mean? Confidence intervals How to test for trends Experiments when each subject receives more than one treatment Alternatives to analysis of variance and the t test based on ranks How to analyze survival data

Download or read book Primer of Statistics written by Sir William Palin Elderton and published by . This book was released on 1910 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Primer of Statistics written by Sir William Palin Elderton and published by . This book was released on 1936 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Primer of Ecological Statistics written by Nicholas J. Gotelli and published by Sinauer Associates, Incorporated. This book was released on 2004 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: Part I: FundamentaIs of Probability and Statistical Thinking. Chapter 1: An lntroduction to Probability. What Is Probability? Measuring Probability. The Probability of a Single Event. Prey Capture by Carnivorous Plants. Estimating Probabilities by Sampling . Problems in the Definition Probability The Mathematics of Probability. Defining the Sample Space. Complex and Shared Events: Combining Simple Probabilities. Probability Calcu1ations: Milkweeds and Caterpillars. Complex and Shared Events: Rules for Combining Sets, Conditional Probabilities. Bayes' Theorem. Chapter 2: Random Variables and Probability Distributions. Discrete Random Variables. Bernoulli Random Variables. An Example of a Bernoulli Trial. Many Bernoulli Trials = A Binomial Randorn Variable. The Binomial Distribution. Poisson Random Variables. An Example of a Poisson Random Variable: Distribution of aRare Plant. The Expected Value of a Discrete Random Variable. The Variance of a Discrete Random Variable. Continuous Random Variables. Uniform Random Variables. The Expected Value of a Continuous Random Variable. Normal Random Variables. Useful Properties of the Normal Distribution. Other Continuous Random Variables. The Central Limit Theorem. Chapter 3: Summary Statistics: Measuresof Location and Spread. Measures of Location. The Arithmetic Mean Other Means. Other Measures of Location: The Median and the Mode. When to Use Each Measure of Location. Measures of Spread. The Variance and the Standard Deviation. The Standard Error of the Mean. Skewness, Kurtosis, and Central Moments. Quantiles. Using Measures of Spread. Some Philosophical Issues Surrounding Summary Statistics. Confidence Intervals. Generalized Confidence lntervals. Chapter 4: Framing and Testing Hypotheses. Scientific Methods. Deduction and lnduction. Moderrn-Day lnduction: Bayesian lnference. The Hypothetico-Deductive Method. Testing Statistical Hypotheses. Statistical Hypotheses versus Scientific Hypotheses. Statistical Significance and P - Values. Errors in Hypothesis Testing. Parameter Estimation and Prediction. Chapter 5:Three Frameworks for Statistical Analysis. Sample Problem. Monte Carlo Analysis. Step 1: Specifying the Test Statistic. Step 2: Creating the Null Distribution. Step 3: Deciding on a One- or Two- Tailed Test. Step 4: Calculating the Tail Probability. Assumptions of the Monte Carlo Method. Advantages and Disadvantages of the Monte Carlo Method. Parametric Analysis. Step 1: Specifyjng the Test Statistic. Step 2: Specifying the Null Distribution. Step 3: Calculating the Tail Probability. Assumptions of the Parametric Method. Advantages and Disadvantages of the Parametric Method. Least-Squares Parameter Estimates 246 Variance Components and the Coefficient of Determination. Hypothesis Tests with Regression. The Anatomy of an ANOVA Table. Other Tests and Confidence IntervaIs. Assumptions of Regression. Diagnostic Tests For Regression. Plotting ResiduaIs. Other Diagnostic Plots. The lnfluence Function. Monte Cado and Bayesian Analyses. Linear Regression Using Monte Cado Methods. Linear Regression Using Bayesian Methods. Other Kinds of Regression Analyses. Robust Regression. Quantile Regression. Logistic Regression. Non-Linear Regression. Multiple Regression. Path AnaIysis. Model Selection Cri teria. Model Selection Methods for Multiple Regression. Model Selection Methods in Path Analysis. Bayesian Model Selection. Chapter 10: The Analysis Of VarianceSymbols and Labels in ANOVA. ANOVA and Partitioning of the Sum of Squares. The Assumptions of ANOVA. Hypothesis Tests with ANOVA. Constructing F- Ratios. A Bestiary of ANOVA Tables. Randomized Block. Nested ANOVA. Two- Way ANOVA. ANOVA for Three- Way and n- Way Designs. Split-Plot ANOVA. Repeated Measures ANOVA. ANCOVA. Random versus Fixed Factors in ANOVA. Partitioning the Variance in ANOVA. After ANOVA: Plotting and Understanding Interaction Terms. Plotting Results from One-Way ANOVAs. Plotting Results from Two- Way ANOVAs. Understanding the lnteraction Term. Plotting Results fram ANCOVAs. Comparing Means. A Posteriori Comparisons. A Priori Contrasts. Bonferroni Corrections and the Problem of Multiple Tests. Chapter 11: The Analysis of Categorical Data. Two- Way Contingency Tables. Organizing the Data. Are the Variables lndependent? Testing the Hypothesis: Pearson's Chi-square Test. An Alternative to Pearson's Chi-Square: The G- Test. The Chi-square Test and the G- Test for R x C Tables. Which Test To Choose? Multi- Way Contingency Tables. Organizing the Data. On to Multi- Way Tables! Bayesian Approaches to Contingency Tables. Tests for Goodness-of-Fit. Goodness-of- Fit Tests for Discrete Distributions. Testing Goodness-of-Fit for Continuous. Distributions: The Kolmogorov-Smirnov Test. Chapter 12: The Analysis Of Multivariate Data. Approaching Multivariate Data. The Need for Matrix Algebra. Comparing Multivariate Means. Comparing Multivariate Means of Two Samples: Hotelling's y2 Test. Comparing Multivariate Means of More Than Two Samples: A Simple MANOVA. The Multivariate Normal Distribution. Testing for Multivariate Normality. Measurements of Multivariate Distance. Measuring Distances between Two IndividuaIs. Measuring Distances Between Two Groups. Other Measurements of Distance. Ordination. Principal Component Analysis 406 Factor Analysis. Principal Coordinates Analysis. Correspondence Analysis. Non-Metric Multidimensional Scaling. Advantages and Disadvantages of Ordination.Classification . Cluster Analysis. Choosing a Clustering Method. Discriminant Analysis. Advantages and Disadvantages of Classification. Multivariate Multiple Regression. Redundancy Analysis.

Download or read book A Primer in Probability written by Kathleen Subrahmaniam and published by CRC Press. This book was released on 2018-10-08 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Somewhat revised/expanded new edition of a problem-oriented introductory undergraduate text, the first edition of which appeared about a decade ago. The author writes with courteous clarity, and imposes only modest demands upon the mathematical skills of her readers. Problems at the end of each of t

Download or read book Primer of Applied Regression Analysis of Variance written by Stanton A. Glantz and published by McGraw Hill Professional. This book was released on 2012-09-01 with total page 980 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applicable for all statistics courses or practical use, teaches how to understand more advanced multivariate statistical methods, as well as how to use available software packages to get correct results. Study problems and examples culled from biomedical research illustrate key points. New to this edition: broadened coverage of ANOVA (traditional analysis of variance), the addition of ANCOVA (analysis of Co-Variance); updated treatment of available statistics software; 2 new chapters (Analysis of Variance Extensions and Mixing Regression and ANOVA: ANCOVA).

Download or read book Primer for Data Analytics and Graduate Study in Statistics written by Douglas Wolfe and published by Springer Nature. This book was released on 2020-09-26 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is specially designed to refresh and elevate the level of understanding of the foundational background in probability and distributional theory required to be successful in a graduate-level statistics program. Advanced undergraduate students and introductory graduate students from a variety of quantitative backgrounds will benefit from the transitional bridge that this volume offers, from a more generalized study of undergraduate mathematics and statistics to the career-focused, applied education at the graduate level. In particular, it focuses on growing fields that will be of potential interest to future M.S. and Ph.D. students, as well as advanced undergraduates heading directly into the workplace: data analytics, statistics and biostatistics, and related areas.

Download or read book Basic Statistics for Laboratories written by William D. Kelley and published by John Wiley & Sons. This book was released on 1992-04-16 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Marketing and regulatory pressures are driving laboratories to adopt statistically valid quality control or quality assurance systems. For the laboratory professional who’s unfamiliar with the statistical tools used in laboratory quality control, Basic Statistics for Laboratories offers guidance to employing basic statistical controls or reports required by regulatory or accrediting organizations, as well as statistical methods which may otherwise be useful in the lab. The book explains, in basic terms, how to set up, maintain, and interpret control charts and other commonly used laboratory statistical tools, and explains their value to the user. Every technique is delivered in its simplest, most basic form. There is step-by-step guidance to method development, validation, comparison of test methods, and quality control for even small samples, without the use of mathematics beyond the high school level. Tests for the significance of differences, presented in "cookbook" format solutions, make it easy for lab professionals to plug in their own data and use tables. You’ll also find exclusive coverage of the problems of asbestos counting laboratories. In addition, the volume presents simple solutions to other problems involving data handling and interpretation, such as the treatment of outliers and how to deal with single or rarely encountered samples. For analysts, test engineers, and laboratory technicians in medical, pathological, environmental, industrial hygiene, and forensic laboratories, Basic Statistics for Laboratories is a timely and essential reference.