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    Welcome to Statistics 2!  This class covers simple and multiple regression, fundamentals of experimental design, analysis of variance methods, and logistic regression.  If time allows, other topics will be selected from the following: Poisson regression, resampling methods, introduction to Bayesian methods, and probability models.  This class includes substantial use of statistical software.  Prerequisite: AP Statistics.

     

    This class is for students who want to continue on in their study of Statistics without involving Calculus.  This is a fairly standard curriculum used by colleges nationwide for students who receive credit for passing the AP Statistics exam (this class has been modeled after such a class at the University of Texas at Austin).  After completing this class students should be able to:

    1. Choose the appropriate statistical model for a particular problem.
    2. Know the conditions that are typically required when fitting various models.
    3. Assess whether or not the conditions for a particular model are reasonably met for a specific dataset.
    4. Have some strategies for dealing with data when the conditions for a standard model are not met. 
    5. Use the appropriate model to make appropriate inferences.
    All assignments, classrooms files, and due dates can be located on the HISD HUB.  Please access your class information there frequently.