

Objectives
of the Unit

Sample Overview
The sample material
for Unit 2 consists of the first two of four investigations of
Lesson 2, "Variability."
Understanding, measuring, and describing variability is a central theme
throughout the curriculum. In these two investigations, students examine
variability using the fivenumber summary and box plots.
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Instructional
Design
Throughout the curriculum,
interesting problem contexts serve as the foundation for instruction.
As lessons unfold around these problem situations, classroom instruction
tends to follow a fourphase cycle of classroom activities—Launch,
Explore, Share and Summarize, and Apply.
This instructional model is elaborated under Instructional
Design.
How the Statistics
and Probability Strand Continues
The second unit
from the statistics and probability strand in Course 1, Patterns
in Chance, introduces
students to sample spaces, probability
distributions, the Addition Rule, simulation, and geometric probability. Important
probabilistic concepts explored include mutually exclusive events and the Law of
Large Numbers.
In
Course 2
Unit 4, Regression and Correlation, students study the
appropriate use of correlation and regression to describe bivariate
association. Students will continue to develop their ability to understand
and visualize situations involving chance (in Unit 8, Probability
Distributions) by
using simulations and mathematical analysis to construct probability
distributions. They study the following topics: Multiplication Rule,
independent and dependent events, conditional probability, probability
distributions and their graphs, waitingtime or geometric distributions,
expected value, and rare events.
In
Course 3
Unit 1, Reasoning and Proof,
students are introduced to more formal statistical reasoning. Students
study inductive and deductive reasoning strategies; principles of logical
reasoning—Affirming the
Hypothesis and Chaining Implications; the relation among angles formed
by two intersecting lines or by two parallel lines and a transversal;
rules for transforming algebraic expressions and equations; design
of experiments including the role of randomization, control groups,
and blinding; sampling distributions; randomization tests; and statistical
significance. In Unit 4, Samples
and Variation,
students extend their understanding of measurement of variation, use
the normal distribution as a model of variation, are introduced to
the binomial distribution and its use in decision making, and are introduced
to probability and statistical inference involved in the control charts
used in industry for statistical process control. (See the CPMP
Courses 14 descriptions.)
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