Examining
Relationships
Regression Facts
YMS3e Chapter 3
3.3: Correlation and Regression Wisdom
Mr. Patterson
Regression Basics
Scatter Plot
The Endangered Manatee
! When describing a Bivariate
Relationship:
! Make a Scatterplot
! Strength, Direction, For
Section 4.1
Transforming to Achieve
Linearity
As weve seen, not all bivariate data can be
represented well by a linear model. The following two
scatterplots are two examples of this.
However, many situations can be TRANSFORMED to
become linear. This is
Section 4.2
Relationships between
Categorical Variables
OVERVIEW:
We can see relations between two or more
categorical variables by setting up tables. Up
to this point, we have studied relations in
which at least the response variable was
quantitative.
The Question of Causation
YMS3e 4.3:Establishing Causation
AP Statistics
Mr. Patterson
Beware the post-hoc fallacy
!
Post hoc, ergo propter hoc.
!
!
!
!
After this, therefore, because of this
Just because something happens after
something else, does
Chapter 5: Producing Data
5.1 Designing Samples
"An approximate answer to the right question
is worth a good deal more than the exact
answer to an approximate question."
John Tukey
Overview
If one wishes to obtain reliable statistical
information from sa
Chapter 5: Producing Data
5.2 Designing Experiments
Overview
There are good techniques for producing data.
There are also bad techniques that produce
worthless data.
Random sampling and randomized comparative
experiments are extremely important and
eff
Chapter 6: Probability
and Simulation
6.1: Simulation
Casino Games
How would you determine the
probability of winning the casino game
of craps?
There are 3 methods we can use to
answer questions involving chance.
3 methods
1. Try to establish the likeli
6.2 Probability Models
It is often important and necessary to provide
a mathematical description or model for
randomness.
Basic Definitions
n
n
Probability: long-run proportion of
repetitions on which an event can occur
Sample Space: set of all possible o
6.3 General
Probability Rules
The most important questions of life
are, for the most part, really problems
of probability.
Pierre-Simon Laplace (1749-1827)
Addition Rule for Disjoint Events
n
n
If they have no outcomes in common, then
P(A or B or C) = P(A
Chapter 7: Random Variables
7.1 Discrete and Continuous
Random Variables
Introduction
n Sample spaces need not consist of numbers
n When we toss four coins, we can record
the outcome such as the count of heads.
n It is convenient to use shorthand notation
Chapter 7: Random Variables
7.2 Means and Variance of
Random Variables
The Tri-State Pick 3
n You choose a 3 digit number
n State chooses a 3 digit number
n Win $500 if they match
Let X be the amount your ticket pays you.
Create a probability distribution
Chapter 8:
The Binomial and
Geometric Distributions
8.1 The Binomial
Distributions
We frequently encounter random phenomena
where there are two outcomes of interest.
n
The coin toss in a football game used to
determine which team gets the choice of
kickin
Chapter 8:
The Binomial and
Geometric Distributions
8.2 The Geometric
Distributions
Getting Started
n
Suppose Alex is bashful and has trouble getting
girls to say Yes when he asks them for a date.
Sadly, in fact, only 10% of the girls he asks
actually agr
Chapter 14
Inference for
Distribution of
Categorical Variables:
Chi-Squared
Chapter Objectives
Understand and Conduct Chi-Square Tests
Goodness of Fit
Homogeneity of Populations
Association/Independence
2
Given a two-way table, compute conditional
di