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This the first module of a networked-based
two module course in the basic ideas of probability and
statistics. The module is intended to provide the
necessary background for teachers of high school statistics. Module
I deals with introductory concepts: descriptive statistics
(central tendency and variation), linear regression (and
correlation), expected value, probability and data
collection.
These modules are closely linked to the textbook, Statistics:
The Craft of Data Collection, Description, and Inference (Monrad,
Stout, and Harner, Moebius Publications, 2002, 3rd edition). The
general pattern for taking the module will consist of reading the
book in hard copy and doing exercises from the book, using Excel
and the graphing calculator supplement to the book. Exercises
and other activities will be conducted in electronic format
(spreadsheet, word processor, calculators, etc.) and submitted to
the instructor via the Internet.
More details on each individual unit are given below:
Interactive Statistics -- Unit 1 Introduction
In this first unit, participants will be exposed to the World
Wide Web as a resource for statistics instruction. Participants
will learn how to use the web as a resource by exploring various
statistics internet sites. Then ways of exploring data using tables
and graphs will be introduced.
Interactive Statistics -- Unit 2 Introduction
In this second unit, participants will be introduced
to centers of data (mean, median, and mode), ways of measuring spread, the
normal distribution, and boxplots.
Interactive Statistics -- Unit 3 Introduction
Unit 3 deals with linear relationships in data by studying
scatterplots, correlation, regression, and the question of causation.
Interactive Statistics -- Unit 4 Introduction
Unit 4 will elaborate on the previous three units as
well as introduce a few new topics. New topics of Unit 4 are experimental
probability, probability models, simulation, box models, and random sampling,
and expected value.
Interactive Statistics -- Unit 5 Introduction
Unit 5 first focuses on learning about probability distributions--specifically
the Binomial, Geometric, Poisson, and Normal distributions. Then issues of
sampling and experimental design are discussed.
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