Graduate students

  • The Research Methods Knowledge Base is a comprehensive web-based textbook that addresses all of the topics in a typical introductory undergraduate or graduate course in social research methods.  It covers the entire research process including: formulating research questions; sampling (probability and nonprobability); measurement (surveys, scaling, qualitative, unobtrusive); research design (experimental and quasi-experimental); data analysis; and, writing the research paper.  It also addresses the major theoretical and philosophical underpinnings of research including: the idea of validity in research; reliability of measures; and ethics.  The Knowledge Base was designed to be different from the many typical commercially-available research methods texts.  It uses an informal, conversational style to engage both the newcomer and the more experienced student of research.  It is a fully hyperlinked text that can be integrated easily into an existing course structure or used as a sourcebook for the experienced researcher who simply wants to browse.

     

    Navigate this source:  http://www.socialresearchmethods.net/kb/contents.php  

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  • Statistics forum for questions/conversations ranging from homework problems in statistics and probability and help using statistical software to statistical research inquiries and career advising.

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  • The Probability Web is a collection of probability resources designed to be especially helpful to researchers, teachers, and people in the probability community.  Web page links on this site include probabilty/statistics books and journals, information on mathematics and statistics-based careers, statistical software, teaching resources on probabilty topics, and more.

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  • The Journal of Statistics Education provides a collection of Java applets and excel spreadsheets (and the articles associated with them) from as early as 1998 on this webpage.

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  • StatCrunch is a web-based package that does a complete range of statistical calculations. Formerly known as WebStat, it provides statistical calculation functions that would be done in most introductory statistics courses, including, but not limited to, creating histograms, pie charts, and boxplots; calculating summary statistics and confidence intervals; and performing hypothesis tests. It allows data to be entered in a spreadsheet style data window or opened from a file. StatCrunch does require a subscription for students and professionals ($13 for 6 months and $23 for 12 months).

    StatCrunchThis allows you to pull data sets contained on many web pages in various forms directly into StatCrunch for analysis.

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  • Big data analysis is explained in this online course that introduces the user to the tools Hadoop and Mapreduce. These tools allow for the parallel computing necessary to analyze large amounts of data.

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  • This is a complete lesson module (including example problems with answers to selected problems) for the purpose of enabling students to: 1) Provide examples demonstrating how the margin of error, effect size, and variability of the outcome affect sample size computations. 2) Compute the sample size required to estimate population parameters with precision. 3) Interpret statistical power in tests of hypothesis. 4) Compute the sample size required to ensure high power when hypothesis testing.
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  • Document (pdf) illustrating a test of normality using an Anderson-Darling test in MINITAB and a test of equality of variances with an F-test in EXCEL.
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  • Presentation that applies the topics of power and sample size to examples in epigenetic epidemiology studies. Step by step solutions using statistical softwares G*Power and STATA are given.
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  • This site did a lot of data visualization on many hot button topics. They provide the raw data that they used to create their graphs at this page. These data sets are kept in Google Doc spreadsheets.
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