Why Statistics?
meaningful questions - systematic methods
General Overview
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“In most mathematics courses, the
problem is solved when you obtain
the numerical answer. In statistics,
the problem is just beginning.”
– Daren Starnes
General Overview

“Statistics is about data. Data are
numbers, but they are not just
numbers. Data are numbers with a
context.”
– YMS, p. xii
General Overview

“All models are wrong. Some
models are useful.”
– George E.P. Box

“There are three kinds of lies: lies,
damned lies, and statistics.”
– Benjamin Disraeli
General Overview

“53.8% of all statistics are made
up.”
– The back of a package of wipes from Hooters
General Overview

“An anonymous sage once defined
a statistician as “one who collects
data and draws confusions.”
– CCMC, p. 1
Statistics vs. Other Math Courses

“The formation of a statistics question
requires an understanding of the
difference between a question that
anticipates a deterministic answer and a
question that anticipates an answer based
on data that vary.”
– ASA, 2005
Statistics vs. Other Math Courses
 Context
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Variability
Estimation
Research Design
Data Collection
Interpretation
Writing
Statistics vs. Other Math Courses

Context
 Variability
 Estimation

Research Design / Data Collection
 Writing
Statistics vs. Other Math Courses

How fast is this car going?
– Leads to a single discreet answer – Mathematical
Thinking

How fast are cars going on I-85 between
I-77 and Concord Mills?
–
Involves Context, Variability, Estimation, Research
Design, and Writing – Statistical Thinking
Why Statistics?

Some understanding of statistics helps
all educational leaders in the current
policy climate.
– Program evaluation
– Emphasis on test scores
– NCLB
– Becoming a reflective practitioner
– Becoming a researcher / practitioner
How Does Statistics Work?

The Population
– The group about which you wish to make
conclusions or generalizations
– Defined by specific characteristics

For our example dataset this semester
– All public school elementary teachers in the U.S.
during the 1999-2000 school year
How Does Statistics Work?

The Sampling Frame
– The best available list of the members of the
population
– Should be as close actual population as possible

For our example dataset this semester
– The list of all public schools in the U.S.
according to the Common Core of Data from the
National Center for Education Statistics (NCES)
How Does Statistics Work?

The Sample
– The group of participants you obtain for your
study
– Should be representative of the population

For our example dataset this semester
– The participants in the Schools and Staffing
Survey, 1999-2000 cohort
– Public school teacher questionnaire, full time only
How Does Statistics Work?
Sample
Population
Who falls in here?
Who falls in here?
Sampling
Frame
How Does Statistics Work?

Parameters
– Quantitative indexes that describe characteristics
of the population
– The population “true scores”, what we would get
if we collected data from the entire population,
the result of conducting a census

Statistics
– Quantitative indexes that describe characteristics
of the sample
– The sample values that become our best guesses,
or estimates, of population “true scores”, called
parameters
Develop the Research Questions
Define the Population to be Studied
Design the Study / Select Methods
Develop a Sampling Plan
Collect Data from the Sample
Calculate Statistics
Use Statistics to Estimate Parameters
Draw Conclusions in Context
Statistical Reasoning

This course is about learning to use
statistical reasoning to help offer some
types of evidence as parts of the
answers to questions about educational
policy:
– Test theories
– Evaluate educational interventions /
strategies
– Answer meaningful educational questions
The Curriculum

Descriptive Statistics / Exploratory
Data Analysis
 Correlation / Regression
 Probability
 Inferential Statistics
– Means
– Proportions / Percentages
Getting Started
 USA
Today polls example
 Electoral Vote tracker site
 Gallup Polls
 The course website
Course Overview

There is more than one way to
unravel a statistics problem.

Connections with most disciplines
abound in statistics.
Course Overview

Make your midterm, final, and class
presentation count for you. Find a
dataset that has utility and meaning
for you.