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.
Chapter 9 Chapter 9 Experimental Research (Reminder: Don’t forget to utilize the concept maps and study questions as you study this and the other chapters.) In this chapter we talk about what experiments are, we talk about how to control for extraneous variables, and we talk about two sets of experimental designs (weak designs and strong designs). (Note: In the next chapter we will talk about middle of the road experimental designs; they are better than the weak designs discussed in this chapter, and they are not as good as the strong designs discussed in this chapter. The middle of the road, or medium quality designs are called quasi-experimental designs.) It is important for you to remember that whenever an experimental research study is conducted the researcher's interest is always in determining cause and effect. The causal variable is the independent variable (IV) and the effect or outcome variable is the dependent variable (DV). The Experiment Independent Variable Manipulation Counterbalancing
Social Reserch Methods Home 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.
Research Methods | AllPsych AllPsych > Research Methods Research Methods By AllPsych Editor AllPsych Editor August 15, 2014Research Methods2014-11-22T01:49:00+00:00 This ten chapter research methods text is written for both undergraduate and graduate students in education, psychology, and the social sciences. It focuses on the basics of research design and the critical analysis of professional research in the social sciences from developing a theory, selecting subjects, and testing subjects to performing statistical analysis and writing the research report. advertisement AddThis Sharing Hide Show AddThis Recommended for you Chapter 3.3 Software Tools Of Research | A... allpsych.com Homosexuality: Nature Or Nurture | AllPsych How To Learn Psychology In Psychol... Sensation And Perception In Psychol... AddThis
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.
Available Research Designs Based on Example Research Questions – SOBT Quantitative Research Designs Avoid research questions with yes or no answers, as they are not particularly interesting. Qualitative Research Designs Design Science References Adeyemo, O. Firari, F. Krear-Klostermeier, K. (2012). Marion, J. Miles, J. Moses, M. Osborne, D. Peacock, C. (2012). Porter, T. Steinwall, M. Stewart, J. Ulrich, Krumschied (2012). Doc. reference: phd_t2_sobt_u03s2_h01_avldesgn.html 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
Rice Virtual Lab in Statistics (RVLS) Partial support for this work was provided by the National Science Foundation's Division of Undergraduate Education through grant DUE 9751307. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Last updated: 07/03/2018 19:56:11 Permissions Permission is granted to link to any portion of the Rice Virtual Lab. The applets in the simulations/demonstrations are hereby in the public domain and can therefore be used without restriction. If you wish to copy and/or distribute any portion of the Case Studies, or the Analysis Lab, please contact David Lane. Credits
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