Free Statistics Book HyperStat Online: An Introductory Statistics Textbook and Discussion of whether most published research is false Click here for more cartoons by Ben Shabad. Other Sources NIST/SEMATECH e-Handbook of Statistical Methods Stat Primer by Bud Gerstman of San Jose State University Statistical forecasting notes by Robert Nau of Duke University related: RegressIt Excel add-in by Robert Nau CADDIS Volume 4: Data Analysis (EPA) The little handbook of statistical practice by Gerard E. Stat Trek Tutorial Statistics at square 1 by T. Concepts and applications of inferential statistics by Richard Lowry of Vassar College CAST by W. SticiGui by P. Online Statistics Education: A Free Resource for Introductory Statistics Developed by Rice University (Lead Developer), University of Houston Clear Lake, and Tufts University OnlineStatBook Project Home This work is in the public domain. If you are an instructor using these materials, I can send you an instructor's manual, PowerPoint Slides, and additional questions that may be helpful to you. Table of Contents Mobile This version uses formatting that works better for mobile devices. Rice Virtual Lab in Statistics This is the original classic with all the simulations and case studies. Version in PDF e-Pub (e-book) Partial support for this work was provided by the National Science Foundation's Division of Undergraduate Education through grants DUE-9751307, DUE-0089435, and DUE-0919818.
Welcome to Seeing Statistics Free Statistics Book Random: Probability, Mathematical Statistics, Stochastic Processes Welcome! Random (formerly Virtual Laboratories in Probability and Statistics) is a website devoted to probability, mathematical statistics, and stochastic processes, and is intended for teachers and students of these subjects. The site consists of an integrated set of components that includes expository text, interactive web apps, data sets, biographical sketches, and an object library. Please read the Introduction for more information about the content, structure, mathematical prerequisites, technologies, and organization of the project. Random is hosted at two sites: www.math.uah.edu/stat/ and www.randomservices.org/stat/. Technologies and Browser Requirements This site uses a number of advanced (but open and standard) technologies, including HTML5, CSS, and JavaScript. Display of mathematical notation is handled by the open source MathJax project. Support and Partnerships Rights and Permissions This work is licensed under a Creative Commons License. Quote
Credit Scoring, Data Mining, Predictive Analytics, Statistics, StatSoft Electronic Textbook "Thank you and thank you again for providing a complete, well-structured, and easy-to-understand online resource. Every other website or snobbish research paper has not deigned to explain things in words consisting of less than four syllables. I was tossed to and fro like a man holding on to a frail plank that he calls his determination until I came across your electronic textbook...You have cleared the air for me. You have enlightened. You have illuminated. You have educated me." — Mr. "As a professional medical statistician of some 40 years standing, I can unreservedly recommend this textbook as a resource for self-education, teaching and on-the-fly illustration of specific statistical methodology in one-to-one statistical consulting. — Mr. "Excellent book. — Dr. "Just wanted to congratulate whoever wrote the 'Experimental Design' page. — James A. Read More Testimonials >> StatSoft has freely provided the Electronic Statistics Textbook as a public service since 1995. Proper citation:
ModernDive Getting Started - For Students This book was written using the bookdown R package from Yihui Xie (Xie 2016). In order to follow along and run the code in this book on your own, you’ll need to have access to R and RStudio. You can find more information on both of these with a simple Google search for “R” and for “RStudio.” An introduction to using R, RStudio, and R Markdown is also available in a free book here (Ismay 2016). It is recommended that you refer back to this book frequently as it has GIF screen recordings that you can follow along with as you learn. We will keep a running list of R packages you will need to have installed to complete the analysis as well here in the needed_pkgs character vector. You can run the library function on them to load them into your current analysis. Colophon The source of the book is available here and was built with versions of R packages (and their dependent packages) given below.
MA121: Introduction to Statistics Probabilities affect our everyday lives. In this unit, you will learn about probability and its properties, how probability behaves, and how to calculate and use it. You will study the fundamentals of probability and will work through examples that cover different types of probability questions. These basic probability concepts will provide a foundation for understanding more statistical concepts, for example, interpreting polling results. Though you may have already encountered concepts of probability, after this unit, you will be able to formally and precisely predict the likelihood of an event occurring given certain constraints. Probability theory is a discipline that was created to deal with chance phenomena. The skill of calculating probability allows us to make better decisions. We will also talk about random variables.
Probability & Statistics Probability & Statistics [Enter Course] Overview: This course introduces students to the basic concepts and logic of statistical reasoning and gives the students introductory-level practical ability to choose, generate, and properly interpret appropriate descriptive and inferential methods. We offer two versions of statistics, each with a different emphasis: Probability and Statistics and Statistical Reasoning. One of the main differences between the courses is the path through probability. In-Depth Description There are two versions of the OLI Statistics course: Probability and Statistics and Statistical Reasoning. Unit 1 Exploratory Data Analysis. Unit 2 Producing Data. Unit 3 Probability. Unit 4 Inference. The course is built around a series of carefully devised learning objectives that are independently assessed. This course contains only the StatTutor lab exercises.
John H. McDonald's home page Research Interests The overall theme of the research in my lab is detecting the effects of natural selection on nuclear genes. This includes detecting the effects of balancing selection and directional selection on variation within populations, variation among populations, and variation among species, and it includes a mix of empirical and theoretical work. Prospective Students I am not seeking a graduate student or post doc for my lab at this time. I may have opportunities for undergraduates with a strong interest in evolutionary biology and a willingness to work independently. I will be glad to advise UD undergrads and others with an interest in evolutionary biology who are planning to apply to graduate schools. Current Projects Adaptation to global warming in enzyme allele frequencies: In the 1970s and 1980s, the technique of allozyme electrophoresis revealed patterns of allele frequency in several species that were associated with latitude. Courses BISC 413: Advanced Genetics Laboratory
StatPrimer (c) B. Gerstman 2003, 2006, 2016 StatPrimer (Version 7.0) (c) B. Burt Gerstman 2003, 2006, 2016 (email) Part A (Introductory) (1) Measurement and sampling [Exercises] (2) Frequency distributions [Exercises] (3) Summary statistics [Exercises] (4) Probability [Exercises] [binomial pmf app] [normal pdf app] (5) Introduction to estimation [Exercises] [simple z/t table] (6) Introduction to hypothesis testing [Exercises](7) Paired samples [Exercises] [two tails of t] (8) Independent samples [Exercises] (9) Proportions [Exercises] (10) R-by-C tables [Exercises] Part B (Intermediate) (11) Variances and means [Exercises] (12) ANOVA [Exercises] (13) ANOVA topics (post hoc comparisons, Levene's test, Non-parametric tests) [Exercises] (14) Correlation [Exercises] (15) Regression [Exercises](16) Risk ratios and prevalence ratios [Exercises] (17) Case-control odds ratios [Exercises] Additional notes Power and sample size [Exercises] How To Know What to Use [Exercises]Approaches Toward Data Analysis Data Files
Online Statistics Education: A Free Resource for Introductory Statistics Developed by Rice University (Lead Developer), University of Houston Clear Lake, and Tufts University OnlineStatBook Project Home This work is in the public domain. If you are an instructor using these materials, I can send you an instructor's manual, PowerPoint Slides, and additional questions that may be helpful to you. Table of Contents 40 Slides Illustrating Concepts Mobile This version uses formatting that works better for mobile devices. Rice Virtual Lab in Statistics This is the original classic with all the simulations and case studies. Version in PDF e-Pub (e-book) Partial support for this work was provided by the National Science Foundation's Division of Undergraduate Education through grants DUE-9751307, DUE-0089435, and DUE-0919818.
Data Science in Education Using R