Transcript Political Research and Statistics

Hypotheses
9/4/2012
Readings
• Chapter 1 The Measurement of Concepts (1423) (Pollock)
• Chapter 2 Measuring and Describing Variables
(Pollock) (pp.28-31)
OPPORTUNITIES TO DISCUSS
COURSE CONTENT
Office Hours For the Week
• When
– Wednesday 11-1
– Thursday 8-12
– And by appointment
Course Learning Objectives
1. Students will learn the research methods
commonly used in behavioral sciences and
will be able to interpret and explain empirical
data.
2. Students will learn the basics of research
design and be able to critically analyze the
advantages and disadvantages of different
types of design.
VARIABLES
Turning things empirical
1.
2.
3.
4.
We experience it
We Define it
We give it value (operationalize)
We develop a hypothesis to explain/predict
what we experienced in step 1
The Relationship Between them
How we measure our Variables
UNITS OF ANALYSIS
Units of analysis
• The unit about which information is collected
and that provides the basis of analysis
• Each member of a population is an element
• Why they are important?
Individual Unit
• The lowest form of data
• People, congressmen,
presidents, etc
Aggregate Data
• A collection of
individual level units
• Often measured in
percentages
• Footprints
The Poor over Time
Immigration over time
The Problem of Access
FALLACIES MADE WITH DATA
Ecological Fallacy
• this arises when an
aggregate/ecological level
phenomenon is used to
make inferences at the
individual level.
• Taking statewide data and
applying to individuals
• Does everyone in MS go
to church?
The Exception Fallacy
• taking one person's
behavior, attributes, etc
and applying it to an
entire group
• Using 1 example to
define group behavior
Examples from Texas
HYPOTHESES
What Is a Hypothesis
• An educated Guess
• These are explicit Statements
• They Try to explain a relationship
• But they are only tentative until tested
The Null Hypothesis
• The Statement of No
Relationship
• What we want to
disprove
• The Basic start of
research
H0
Correlative Hypothesis
• “there is a relationship
between x and y”
• A very weak statement
Positive Hypothesis
• A directional hypothesis
• “as the independent
variable increases, the
dependent variable
increases”
Positive Relationship
Negative Relationship/Hypothesis
• “As the independent
variable increases, the
dependent variable
decreases”
• Also called an inverse
hypothesis
An Example
Logarithmic
• Y=log(x)
• The dependent variable
changes rapidly,
followed by less change
An Example
Curvilinear
• The Relationship forms
a curve!
• The dependent variable
increases to a point,
and which point it
begins to decrease
The Laffer Curve
• The Debate over taxes
• Ben Stein
Fuel Efficiency
Hulk Hogan
• Roddy Piper (4:44)
• King Kong Bundy (2:56)
More
Stating a hypothesis
There is a _____(direction)________relationship
between ________and ____________
CHARACTERISTICS OF GOOD
HYPOTHESES
Good Hypotheses are Empirical
• Something that we can Measure
Good Hypothesis are
Generalizable
• Apply to more than one
case
Specific
• Always State a direction
• Always identify the iv and
the d.v.
• Avoid the correlative
hypothesis
Good Hypotheses are Plausible
• There needs to be a
Real world justification
for why they are related
• If Chewbacca lives on
Endor, you must acquit
Good Hypotheses are Testable
• You have to be able to test your hypothesis or
it is just speculation.
Non-Tautological
• Your independent and dependent variables
are separate concepts
A Test of Scientific Knowledge
A CAUSAL HYPOTHESIS
What is a causal hypothesis?
• The Boldest Hypothesis
out there
• A relationship that will
occur 100% at all times,
no exceptions
• Difficult to Prove
To Prove a Causal Hypothesis
1. A Change in the Independent Variable will
always cause a change in the dependent
variable.
2. A change in X always precedes a change in Y
3. X is necessary and sufficient to cause a
change in Y
Causality is the heart of scientific
knowledge!