Download Exam Review - Blogs @ Suffolk University

Exam 1 Review
GOVT 120
Review: Levels of Analysis
Theory: Concept 1 is related to Concept 2
Hypothesis: Variable 1 (IV) is related to Variable 2 (DV)
Operational Definition:
IV: Definition of Cause
DV: Definition of Effect
Types of Hypotheses (19)
Types of Hypotheses:
Univariate: making a statement about only one property or variable. (19)
Multivariate: a statement about how two or more variables are related.
Most hypotheses are multivariate and
Directional: that is, they suggest not only how the variables are
related
but what the direction of the relationship is. (19)
Null Hypothesis: There is in fact no relationship between the stated
independent and dependent variables.
Hypothesis
Hypothesis: Variables
(IV) Independent Variable: the cause of something
(DV) Dependent Variable: the effect
It is not always easy to determine the IV and DV.
Control Variables: when they are used the intent is to ensure their effects are
excluded.
…
Types of Hypotheses (19)
Types of Directional Relationships: Positive/Negative
Positive: variables move in the same direction:
Example:
1. As income rises, so does voting,
2. As income drops, so does voting.
Negative (or Inverse): Variables move in opposite directions:
Example:
1. As income rises, homelessness drops.
EXAMPLES: Levels of Research: (18)
Hypothesis:
IV: Cause
Positive:
IV: Cause
DV: Effect
They go up together.
DV: Effect
They go down together.
EXAMPLES: Levels of Research: (18)
Hypothesis:
IV: Cause
Negative:
IV: Cause
DV: Effect
The variables move in opposite directions. They have
an inverse relationship to each other .
DV: Effect
Examples of IV and DV
Hypothesis: The better the state of the economy, the greater the proportion
of votes received by the party of the president.
Independent Variable: State of the Economy
Dependent Variable: votes
Direction: positive
Hypothesis: The more negative the advertising in a Senatorial campaign, the
lower the turnout rate.
Independent Variable: negativity of ads
Dependent Variable: turnout
Direction: negative
Examples of IV and DV:
Hypothesis: Media attention is necessary for a candidate to succeed in a
primary election.
Independent Variable: media attention
Dependent Variable: electoral success
Direction: positive
Hypothesis: Southern states have less party competition than Northern
states.
Independent Variable: region
Dependent Variable: party competition
Direction: negative
Three (3) Requirements of Causality
1) Correlation: two things tend to occur at the same time (not sufficient
to establish causation)
Examples:
Whenever there is a foreign policy crisis, presidential popularity
increases
If Catholic, then more likely to oppose abortion.
2) Time Order: cause has to happen before the effect.
3) Non-Spuriousness: to make sure any correlation we observe
between the independent and dependent variables is not caused by
other factors.
…
The Quasi Experimental (Natural Experiment)
2) Quasi Experimental It is also called the before and after test: you compare
the DV (a Pretest and Posttest) before and after the IV has been
applied.
Differs from Experimental Design in several ways:
Groups are not assigned (we observe some happen, and then go back and
sort into experimental and control groups.) Requires a Pretest of DV so
amount of change can be measured.
…
Quasi Experimental Design
Meeting Conditions of Causality:
Quasi Experimental
Correlation: change between pretest and post-test has to be significant
(indicating IV had an effect)
Time Order: includes measure of DV before and after IV.
Non-Spurious: effect of all outside forces is theoretically equal on all subjects.
(they are all exposed to same amount of TV ads, thus any changes comes
from the IV)
• …
The Nature of Social Science Research
Using Numbers in Political Research: Levels of Measurement
Numbers serve important functions for researchers, depending on the level of
measurement employed.
Nominal: Refers to discrete or mutually exclusive categories. Individual cases can
only fit into one category at a time. Used to classify, categorize or label.
Example: party affiliation, voter, non-voter.
Ordinal: Involves the ranking or ordering of cases in terms of the degree to
which they possess a certain characteristic.
Example: Social class, Measurements of attitudes.
Interval-Ratio: Measurements for all cases are expressed in the same units. There
are equal intervals between points on a scale and either a real or theoretical zero
point.
Example: Income, temperature, SAT scores, weight
Measures of Central Tendency
Measures of Central Tendency: Averages
Mean: (Applies to Interval)
The mean is average: is calculated by adding up all of the individual values
and dividing by the number of cases. Can only be computed for Interval
Data.
Median: (Applies to Ordinal and Interval)
Median is the middle: “half cases have higher values and half have lower
values.” Often used to calculate income.
Mode: (Applies to Nominal)
It refers to the “most frequently occurring value or category.”
Skewness
__
LEFT
+
RIGHT
LEFT
RIGHT
Source: http://www.websters-online-dictionary.org/definitions/skewness?cx=partner-pub-0939450753529744%3Av0qd01-tdlq&cof=FORID%3A9&ie=UTF-8&q=skewness&sa=Search#922
16
Types of Sampling
Probabilistic Sampling (Random):
Types: Random, systematic, stratified, cluster
Random (most common): everyone has a equal and independent chance
of being selected.
Challenges:
Telephone sampling
Not everyone has a phone
Not everyone is listed
Busy street
Not random: Not typical of the population.
Disadvantages of Surveys (44)
Here are some the disadvantages of polls:
1) Poor response rates.
2) Reactivity: people react to the fact that they are being studied.
3) Resources needed to conduct poll.
4) Meaning of terms change over time (think of polls conducted since
1952)
5) Response Set: disinterested respondents complete poll without much
concern.
6) Challenges of being random.