Final Stuff

Question 1

Random Sampling

Answer 1

A sample in which everyone in your sampling frame has an equal chance of being selected

Question 2

Simple Random Sample

Answer 2

A basic sampling method where a group of subjects (sample) is selected for study from a larger population, and each member of the population has an equal chance of being selected

Question 3

Stratified sample

Answer 3

A type of sampling that uses a technique in which different subcategories of a sample are identified and then randomly selected

Question 4

Proportional Stratified Random Sample

Answer 4

A type of sampling that uses a technique in which different subcategories of a sample are identified and then selected PROPORTIONAL to the population

Question 5

Cluster Sampling

Answer 5

A type of sampling in which clusters, or groups, are identified that are representative of the entire population, and then sampled randomly within each cluster, letting each cluster represent the population

Question 6

Nonrandom Sampling

Answer 6

Sample that is not generalizable to the population, sample that is not a random sample

Question 7

Convenience Sample

Answer 7

A group of people that is easy to access

Question 8

Volunteer Sample

Answer 8

Consists of people who are willing to volunteer for a study

Question 9

Snowball Sampling

Answer 9

Study participants make referrals to other to other potential participants`

Question 10

Reliability

Answer 10

The ability of a measure to produce the same results if replicated

Question 11

Validity

Answer 11

Accuracy of a measure, in terms of measuring intended constructs or observations

Question 12

Test-retest Reliability

Answer 12

A reliability method in which the same measure is given to the same people at two different times

Question 13

Alternate form reliability

Answer 13

A reliability method to determine if the order in which the items in a measure are presented affect the ways in which people respond

Question 14

Split-half reliability

Answer 14

A means of evaluating internal consistency of a scale that compares one randomly selected half of a scale from the other randomly selected half of the scale

Question 15

Item total reliability

Answer 15

A means of evaluating internal consistency of a scale that compares the total score for a scale with individual items for the same scale

Question 16

Inter-coder reliability

Answer 16

An indicator of how similarly coders are coding content, both in terms of identifying units of analysis and in the contextual labels they ascribe to those units

Question 17

Reliability Statistics examples

Answer 17

Cronbach’s Alpha (for Alpha risk worldview 1), Scott’s Pi (For worldview 2 inter-coder reliability)

Question 18

Face Validity

Answer 18

A type of validity consideration in which measures, or procedures, are looked at and questioned if they make sense at face value

Question 19

Criterion Validity

Answer 19

A type of validity consideration that deals with how a particular measure holds up when compared to some outside criterion

2 types:
-Predictive Validity & Concurrent Validity

Question 20

Predictive Validity

Answer 20

How well a measure predicts something will happen in the future.

Question 21

Concurrent Validity

Answer 21

How well a scale measures up against another scale that has been demonstrated to measure the exact same thing

Question 22

Convergent Validity

Answer 22

When two measures you expect to be related are shown to be positively statistically related

e. g.,
- Attitude toward Same -Sex marriage & Attitude toward homophobia measures end up being positively related

Question 23

Discriminant Validity

Answer 23

When two measures you expect to be negatively related (opposite to each other) are shown to have a negative statistical relationship

Question 24

History (validity)

Answer 24

A validity issue where something totally unrelated to your study happened at a particular time, and may have affected the responses

Question 25

Maturation (Validity)

Answer 25

A validity issue dealing with the fact that subjects can change over time, which can affect their responses to the measures a researcher is interested in

Question 26

Testing Validity

Answer 26

A validity threat where if someone is more familiar or more comfortable with a series of questions or items, they may respond differently

Question 27

Instrumentation Validity

Answer 27

A validity threat that deals with differences that are observed at two different times in which different instruments are used

Question 28

External Validity

Answer 28

Are your findings valid among the population you’re testing?

Proper sampling ensures that you are appropriately representing whoever you say you are representing

Question 29

Z-test (when to use it)

Answer 29

o A large “n” (sample size) (technically 30+, but Nick says truly 100+)
o Knowledge of the population parameters
o Random selected sample
o Normally distributed DV
o Interval/Ratio DV
o Nominal iv ***
- When the Standard deviation of the population is giving

Question 30

T-test (in general)

Answer 30

• Used when:
o You want to compare two groups
o Your distribution is normal-ish
• Parametric Test
o You have an Interval or Ratio DV
o T distribution changes shape depending on the degrees of freedom you have
• Degrees of Freedom
o (n-k)
• n=the number of events observed
• k= the number of independent samples being compared
o The degrees of freedom in our sample tells us the shape of our probability
• Takes out random things so we don’t over extend our parameters
• Adjusts the probability curve so we can see if its statistically significant
• This provides us with a specific critical value based on our sample size

Question 31

One sample t-test

Answer 31

Compares a sample to a population

Question 32

Independent Samples T-test

Answer 32

Compares two samples that cannot overlap

e.g., the effect of derogatory campaign ads on republicans and democrats

Question 33

Dependent Samples T-test

Answer 33

Looks at the differences between two matched samples

e.g., how privates communicate with their officers between various different squads of the army

Question 34

Univariate Anova

Answer 34

ls sometimes called a “one-way” ANOVA
o Allows us to compare multiple groups defined by variation in a nominal IV, at the same time
• DV is still continuous (Ratio or Interval)

Question 35

Factorial Anova

Answer 35

allows for Multiple IVs or moderators
• Multiple IV’s (or IV + Moderator) that are interacting and having a simultaneous impact on the Dependent Variable
• Higher the test statistic, the stronger the relationship