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Summer 2013 > CJUS 3101 Final > Flashcards

CJUS 3101 Final Flashcards

0
Q

Sampling Frame

A

Probability Sample

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1
Q

Equal chance of selection

A

Probability Sample

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2
Q

Random Chance or selection

A

Probability Sample

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3
Q

Generalizability

A

Probability Sample

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4
Q

Unknown chance of selection

A

Non-Probability Sample

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5
Q

No sampling frame

A

Non-Probability Sample

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6
Q

Non-random selection - selected for a reason

A

Non-Probability Sample

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7
Q

Non-generalizable

A

Non-Probability Sample

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8
Q

All of the individuals or cases we are interested in studying

A

Population

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9
Q

A subset or smaller group selected from our population

A

Sample

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10
Q

The process of applying the results we get from our sample to the population

A

Generalization

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11
Q

This is what sampling sets out to achieve

A

Representative Sample

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12
Q

Boundaries of the population being sampled

A

Parameters

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13
Q

All of the people or elements of the population have an equal chance of being selected for the sample

A

Probability Sampling

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14
Q

Gold standard of sampling, everyone in the population has an equal and independent chance of being selected for the sample

A

Simple random sampling

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15
Q

a list of everyone or object in the population

A

Sampling Frame

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16
Q

A modified form of SRS. Instead of the selection being random there is a patter

A

Systematic Sampling

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17
Q
  • Define target population

- Determine the desired sample size

A

Sampling Interval

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18
Q

How do you find sampling interval?

A

Divide your sample size into the number of persons by the number of persons in your sampling frame
- If you had 100 persons in your sampling frame and wanted to sample 20 persons
100
—– = 5
20

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19
Q

Use this type of sampling when the variable is rare and would be hard to obtain through SRS

A

Stratified Sampling

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20
Q

The population is divided into subgroups and you select from each of the subgroups

A

Stratified Sampling

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21
Q

This type of sampling is utilized in situations when you cannot construct a sampling frame because it is to difficult.

A

Cluster Sampling

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22
Q

Use this type of sampling when you have more than one sampling frame of clusters

A

Multistage cluster sampling

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23
Q

as our sample size increases the sampling distribution will equal the mean of the population distribution

A

Central Limit Theorem

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24
The standard deviation of the sampling distribution
Standard Error
25
The range of values that probably include the real value
Confidence Interval
26
a * denotes or means that our estimate is probably correct and not due to chance or sampling error.
Statistical Significance
27
This is when we conclude that our statistic represents the population when in fact it does not.
Type 1 Error
28
The elements do not have an equal chance of being selected
Non-Probability Sampling
29
This is where you simply use subjects that are easy or convienent for you to use
Convenience Sampling
30
This is where the researcher selects individuals based on the researchers knowledge or professional judgement
Judgmental Sampling
31
This is a method typically used with unknown or rare populations that are difficult to locate, situations where it would be impossible to construct a sampling frame.
Snowball Sampling
32
The way this technique works is that you find one or more subjects that you want to study and ask them to refer you to others.
Snowball Sampling
33
Is an association between two variables. they occur together
Correlation
34
A and B tend to be observed at the same time
Correlation
35
You need to have an association in order to argue for this
Causality
36
A causes B
Causation
37
What are the 3 criteria to say that two variables have a casual relationship
1. The two variables must be correlated. 2. Time ordering 3. Non - Spuriousness
38
A situation where it looks like two variables are related to one another, but in fact they are not
Spuriousness
39
gives us a way of summarizing the differences so that we can compare the strengths of different tables or variables
Strength Measure
40
measure the strength of the association between two nominal and ordinal variables
Crosstabulation Table
41
Something that is required or must be present in order for the effect to occur. A must occur if B is to occur.
Necessary Cause
42
Guarantees the effect will occur
Sufficient Cause
43
This type of cause increases the chances that something will happen
Contributory cause
44
If x does not happen, y will not happen
Necessay Cause
45
If x happens, Y will happen
Sufficient cause
46
If x happens, Y may happen or is more or less likely to happen
Contributory Cause
47
An experiment where you have a group that receives treatment and one that does not and see what happens
Classical Experiment
48
The independent variable in a classical experiment
The treatment
49
The group that receives treatment is the
experimental group
50
The group that does not receive treatment
control group
51
This is where we collect baseline data
pretest
52
this is where we measure the dependent variable after treatment
posttest
53
In order for the design to work it is crucially important that your experimental and control groups are equivalent at the beginning of the experiment. How do you ensure this?
Random Assignment
54
threats or challenges to our findings and to our potential conclusions that a causal relationship may or may not exist
Internal Validity
55
These are events that happen during the course of the experiment. These are things that occur outside of the experiment
History
56
These are changes that take place in the subjects during the course of the experiment. This includes biological, psychological, and physiological changes.
Maturation
57
Refers to the tendency of subjects to move toward the average over time
statistical regression
58
This is really just attrition or persons dropping out of the experiment
Experimental mortality
59
refers to the measures of your variables; can refer to when your measures lack reliability or validity
instrumentation
60
This is where the subjects learn through their exposure to the pretest learn how to do better on the post test
Testing Effects
61
This is where the treatment spills over from the experimental group to the control group could be communication
Design Contamination
62
assessment of wether our results are applicable to other groups
External Validity
63
situation where the subjects may be exposed to more than one treatment or independent variable
Multiple treatment influence
64
refers to subjects reacting to the fact that they are in an experiment or research project
reactive effects
65
this is where you try your best to get a similar control group but they are not randomly assigned
non-equivalent control group design
66
this is where we observe our dependent variable over time both before the independent variable is introduced
interrupted time series design
67
surveys that survey respondents at one point in time
Cross - Sectional
68
surveys conducted over time
longitudinal
69
these collect information on a variable over time
trend study
70
this study follows a group that shares the same characteristic over time
cohort study
71
study that follow the same individuals over time and collect data at intervals
panel study
72
Levels of measurement | NOIR
1. Nominal 2. Ordinal 3. Interval Ratio

Summer 2013 (1 decks)

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