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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
Q

The standard deviation of the sampling distribution

A

Standard Error

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25
Q

The range of values that probably include the real value

A

Confidence Interval

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26
Q

a * denotes or means that our estimate is probably correct and not due to chance or sampling error.

A

Statistical Significance

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27
Q

This is when we conclude that our statistic represents the population when in fact it does not.

A

Type 1 Error

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28
Q

The elements do not have an equal chance of being selected

A

Non-Probability Sampling

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29
Q

This is where you simply use subjects that are easy or convienent for you to use

A

Convenience Sampling

30
Q

This is where the researcher selects individuals based on the researchers knowledge or professional judgement

A

Judgmental Sampling

31
Q

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.

A

Snowball Sampling

32
Q

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.

A

Snowball Sampling

33
Q

Is an association between two variables. they occur together

A

Correlation

34
Q

A and B tend to be observed at the same time

A

Correlation

35
Q

You need to have an association in order to argue for this

36
Q

A causes B

37
Q

What are the 3 criteria to say that two variables have a casual relationship

A
  1. The two variables must be correlated.
  2. Time ordering
  3. Non - Spuriousness
38
Q

A situation where it looks like two variables are related to one another, but in fact they are not

A

Spuriousness

39
Q

gives us a way of summarizing the differences so that we can compare the strengths of different tables or variables

A

Strength Measure

40
Q

measure the strength of the association between two nominal and ordinal variables

A

Crosstabulation Table

41
Q

Something that is required or must be present in order for the effect to occur. A must occur if B is to occur.

A

Necessary Cause

42
Q

Guarantees the effect will occur

A

Sufficient Cause

43
Q

This type of cause increases the chances that something will happen

A

Contributory cause

44
Q

If x does not happen, y will not happen

A

Necessay Cause

45
Q

If x happens, Y will happen

A

Sufficient cause

46
Q

If x happens, Y may happen or is more or less likely to happen

A

Contributory Cause

47
Q

An experiment where you have a group that receives treatment and one that does not and see what happens

A

Classical Experiment

48
Q

The independent variable in a classical experiment

A

The treatment

49
Q

The group that receives treatment is the

A

experimental group

50
Q

The group that does not receive treatment

A

control group

51
Q

This is where we collect baseline data

52
Q

this is where we measure the dependent variable after treatment

53
Q

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?

A

Random Assignment

54
Q

threats or challenges to our findings and to our potential conclusions that a causal relationship may or may not exist

A

Internal Validity

55
Q

These are events that happen during the course of the experiment. These are things that occur outside of the experiment

56
Q

These are changes that take place in the subjects during the course of the experiment. This includes biological, psychological, and physiological changes.

A

Maturation

57
Q

Refers to the tendency of subjects to move toward the average over time

A

statistical regression

58
Q

This is really just attrition or persons dropping out of the experiment

A

Experimental mortality

59
Q

refers to the measures of your variables; can refer to when your measures lack reliability or validity

A

instrumentation

60
Q

This is where the subjects learn through their exposure to the pretest learn how to do better on the post test

A

Testing Effects

61
Q

This is where the treatment spills over from the experimental group to the control group could be communication

A

Design Contamination

62
Q

assessment of wether our results are applicable to other groups

A

External Validity

63
Q

situation where the subjects may be exposed to more than one treatment or independent variable

A

Multiple treatment influence

64
Q

refers to subjects reacting to the fact that they are in an experiment or research project

A

reactive effects

65
Q

this is where you try your best to get a similar control group but they are not randomly assigned

A

non-equivalent control group design

66
Q

this is where we observe our dependent variable over time both before the independent variable is introduced

A

interrupted time series design

67
Q

surveys that survey respondents at one point in time

A

Cross - Sectional

68
Q

surveys conducted over time

A

longitudinal

69
Q

these collect information on a variable over time

A

trend study

70
Q

this study follows a group that shares the same characteristic over time

A

cohort study

71
Q

study that follow the same individuals over time and collect data at intervals

A

panel study

72
Q

Levels of measurement

NOIR

A
  1. Nominal
  2. Ordinal
  3. Interval Ratio

Summer 2013 (1 decks)

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