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Lecture Examples

  • The goal of WISE is to provide students and teachers of statistics easy access to a wide range of resources that are freely available on the internet. We invite you to explore our website and enjoy many wonderful statistical materials from around the world.

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  • This text was written for an introductory class in Statistics suitable for students in Business, Communications, Economics, Psychology, Social Science, or liberal arts; that is, this is the first and last class in Statistics for most students who take it. It also covers logic and reasoning at a level suitable for a general education course.  SticiGui provides text, interactive tools, lecture videos, sample exam reviews, and more for a course in basic statistical concepts.  

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  • This page supports an in-class exercise that highlights several key Bayesian concepts. The scenario is as follows: a large paper bag contains pieces of candy with wrappings of different color, and we are interested in learning about the unknown proportion of yellow-wrapped pieces of candy. After completing the exercises, we will be familiar with the following concepts and ideas: probability distributions can quantify degree of beliefprior distributionposterior distributionsequential updatingconjugacy, Cromwell’s Rule (http://en.wikipedia.org/wiki/Cromwell's_rule), the data overwhelm the prior, Bayes factors, Savage-Dickey density ratio, sensitivity analysiscoherence.

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  • This page presents a series of tutorials and interdisciplinary case studies that can be used in a variety of blended as well as brick-and-mortar courses. The materials can be used in introductory level data science courses as well as more advanced data science or statistics courses.  These materials assume that students have a basic prior knowledge of R or Rstudio.

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  • The goal of this text is to provide a broad set of topics and methods that will give students a solid foundation in understanding how to make decisions with data. This text presents workbook-style, project-based material that emphasizes real world applications and conceptual understanding. Each chapter contains:

    • An introductory case study focusing on a particular statistical method in order to encourage students to experience data analysis as it is actually practiced.
    • guided research project that walks students through the entire process of data analysis, reinforcing statistical thinking and conceptual understanding.
    • Optional extended activities that provide more in-depth coverage in diverse contexts and theoretical backgrounds. These sections are particularly useful for more advanced courses that discuss the material in more detail. Some Advanced Lab sections that require a stronger background in mathematics are clearly marked throughout the text.
    • Data sets from multiple disciplines and software instructions for Minitab and R.

    The text is highly adaptable in that the various chapters/parts can be taken out of order or even skipped to customize the course to your audience. Depending on the level of in-class active learning, group work, and discussion that you prefer in your course, some of this work might occur during class time and some outside of class. 

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  • Learn to distinguish between exponential and logistic growth of populations, identify carrying capacity, differentiate density-dependent and density-independent limiting factors, apply population models to data sets and determine carrying capacity from population data. Make predictions on graphs and interpret graphical data to analyze factors that influence population growth.

    This link includes a lesson plan, assessment materials, and access to SmartGraphs, a software that helps students create and interpret graphs.

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  • Statistics and probability concepts are included in K–12 curriculum standards—particularly the Common Core State Standards—and on state and national exams. STEW provides free peer-reviewed teaching materials in a standard format for K–12 math and science teachers who teach statistics concepts in their classrooms.

    STEW lesson plans identify both the statistical concepts being developed and the age range appropriate for their use. The statistical concepts follow the recommendations of the Guidelines for Assessment and Instruction in Statistics Education (GAISE) Report: A Pre-K-12 Curriculum Framework, Common Core State Standards for Mathematics, and NCTM Principles and Standards for School Mathematics. The lessons are organized around the statistical problemsolving process in the GAISE guidelines: formulate a statistical question, design and implement a plan to collect data, analyze the data by measures and graphs, and interpret the data in the context of the original question. Teachers can navigate the STEW lessons by grade level and statistical topic.

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  • In the "Mathematics & Statistics" section on the "Faculty Showcase" tab, one can find a free, online statistics textbook (and link to other text resources) along with multiple professors' accounts of how they use this text in their respective classrooms.  On each professor's page is a description of the course taught, what caused each instructor to switch texts, how the text/course material has been received by students, and a sample assignment/syllabus from the course.  This is a wealth of information for those looking to switch books or gain insight into other professors' classes.

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  • This site is a description of the mathematics behind survival analysis. It starts with a definition of the survival function. Then it discusses estimating the survival function with the Kaplan-Meier curve.  Then it discusses comparing survival curves. Finally, there is a discussion of Cox Proportional Hazards regression analysis.

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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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