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  • Correspondence analysis is a method allowing you to describe synthetically a contingency table in which homogeneous individuals are classified on two criterias (or categorical variables, continuous ones being usable if discretized).  This resource tells how it can be used, graphical representations of this process, and gives examples of it in action. 

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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 ARTIST website provides a variety of assessment resources for teaching first courses in statistics. ARTIST's goal is to help teachers assess statistical literacy, statistical reasoning, and statistical thinking in their statistics classes. Registration is required to use assessment materials.

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  • Factual is the location data company the world’s most valuable brands and technology companies trust to understand and intelligently grow their businesses.

    Data is the currency for the new economy, and location data is driving smarter digital products, marketing and business decisions. Our world is now mobile, computing is everywhere, and the power of location data is changing everything — the way we get around, the way we interact with brands, the way we solve problems and the way we discover new services and access information. Location data is changing the way we experience the world.

    Factual provides product and engineering teams, marketers and data analysts access to the world’s most trusted, accurate and comprehensive data on places and people worldwide, transforming products, advertising and businesses with data that puts everything in context.

    Information about working for Factual can be found here:  https://www.factual.com/company/careers/#career 

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  • CODAP provides an easy-to-use web-based data analysis platform, geared toward middle and high school students, and aimed at teachers and curriculum developers. CODAP can be incorporated across the curriculum to help students summarize, visualize and interpret data, advancing their skills to use data as evidence to support a claim.

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  • This site is a government-run repository of information on current and completed clinical trials. Users can search for clinical trials by disease type and also by whether the trial is currently recruiting. Then a detailed description of the trial is given. This can be used in a classroom setting to discuss design issues and ethical issues with clinical trials.

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  • A resource providing information about what the sample size is, what factors the sample size depends on, and how it can be determined,
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  • Resource providing information about: computation of the sample size and the assumptions that must be made to do so. Several examples are given with different conditions in each, and a table showing minimum sample sizes for a two-sided test.
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  • Article that explains why comparing statistical significance, sample size and expected effects are important before constructing and experiment.
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  • If you plan to use inferential statistics (e.g., t-tests, ANOVA, etc.) to analyze your evaluation results, you should first conduct a power analysis to determine what size sample you will need. This page describes what power is as well as what you will need to calculate it.
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