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Old Degree Communication Research Methods > APA, Ch. 5, 7, 8, 9 > Flashcards

APA, Ch. 5, 7, 8, 9 Flashcards

0
Q

A sample from a population is called?

A

Sampling

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1
Q

Parts of a research paper

A

Structure-content-citation rules

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2
Q

The ultimate goal of a sample is to?

A

Generalize (external validity + represent)

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3
Q

Is the accuracy with which the results of an investigation maybe generalized to a different group from that one study

A

External validity

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4
Q

When an investigator is interested in studying a group of people with particular characteristics of interest, that group is known as a

A

Population

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5
Q

We might instead select a subset of the population or universe thought to represent the entire group, a subset known as a

A

Sample

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6
Q

Is the degree to which the samples parameters DIFFER from the parameters of the population from which it was selected

A

Sampling error

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7
Q

There are two sampling methods

A

Probability sampling and nonprobability sampling

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8
Q

Is it generally most preferred by researchers. It involves the selection of elements from a population or universe in accordance with some set of mathematical rules, thereby permitting calculation of the probability of sampling error.

A

Probability sampling

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9
Q

Is the most elementary form of probability sampling. Each element in the population or universe is afforded an equal opportunity of being selected to the sample.

SRS

A

Simple random sampling

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10
Q

The second variety of probability sampling, like simple random sampling, requires a complete sampling frame, from which every element is selected following a random start

A

Systematic sampling

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11
Q

Like the previous two techniques, ______ requires the generation of a complete sampling frame. It’s particular advantage, however, is that it permits the researchers some assurance that elements with particular characteristics are included in the sample.

Organizing the elements in the sampling frame into subsets based on some characteristics of interest, or using one of the previous two techniques to select a proportional representation from each subset to the sample.

A

Stratified sampling

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12
Q

Is a probability sampling technique that is particularly useful when dealing with a very large target population or universe when it would be inconvenient or impossible to generate a complete sampling frame of elements.

The choices of elements are continuously narrowed until a complete sampling frame becomes possible, then the final elements are chosen from the sampling frame in accordance with one of the previous three sampling techniques

MCS

A

Multistage cluster sampling

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13
Q

While most researchers prefer probability sampling techniques, there are numerous occasions went non-probability must be used

A

Nonprobability sampling

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14
Q

How can we improve sampling?

A

We can replicate (different place, different people, different time)

We can use theory or logic to support the claim

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15
Q

Based on mathematical rules

A

Probability sampling

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16
Q

Uses some form of random selection-requires a complete frame.

A

Probability sampling

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17
Q

n = sample size,

A

Systematic sampling

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18
Q

Uses proportional reduction Tatian’s of a certain valuable(Gender, ethnicity, or age)

Males = 60%, females = 40%

A

Stratified sampling

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19
Q

Separate the population into mutually exclusive sets (strata)

Example = sex-male •female • draw random samples from each stratum by using one of the previous two techniques

A

Stratified sampling

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20
Q

Useful for a very large target population-when it seems impossible to generate a complete sampling form

A

Multistage cluster sampling

MCS

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21
Q

Not based on probability (no mathematical rules, not random

A

Nonprobability sampling

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22
Q

Availability sampling, relies on a available sample

A

Convenience sampling

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23
Q

Judgmental sampling, selecting sample based on specific characteristics of interest to the researcher.

Example = topic-combination effectiveness in the successful business.

IBM or Microsoft because of success

A

Purposive sampling

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24
Q

Selecting sample according to some quotas-but not randomly. Represents major characteristics of population (ethnicity, gender) by sampling proportional amount of each.

A

Quota sampling

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25
Q

Network sampling. One person recommends another, who recommends another, who recommends another. We use when = hard-to-reach populations.

A

Snowball sampling

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26
Q

Less effort, less time, less resources.

A

Nonprobability sampling

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27
Q

Limitations? Possible to misrepresent population. Cannot estimate the sampling error, which may cause potential problems in generalizing.

A

Nonprobability sampling limitations

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28
Q

The gap or difference between the nature of the population

A

Big circle = population small circle = with in population-sample

Really big population, really small sample = big gap!

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29
Q

If people in population are similar to each other-possible to select any element that represents the population.

A

Homogeneity

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30
Q

If people are dissimilar - samples must increase in size to reduce the likelyhood of error

A

Heterogenous

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31
Q

The variables expected to influence a change in another variable

A

Independent variable

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32
Q

Those expected to change as a result of the actions of the independent variables

A

Dependent variables

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33
Q

All other variables that might somehow influence the relationship between the independent and Dependant variables, those extraneous to the relationship, are called

A

intervening variables

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34
Q

While another group receives imposed treatment, and is referred to as the

A

Control group

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35
Q

In many cases one or more of the groups receives some level of the independent variable, or some treatment, and is referred to as the

A

Treatment group

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36
Q

We have two groups, each receiving some form of treatment, whether it be lecture or discussion, and those groups are compared with one another, and are therefore known as

A

Comparison groups

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37
Q

Prior to the imposition of the independent variable, all the groups were equivalent with regard of the dependent variable. This assumption is referred to as

A

Group equivalence

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38
Q

Participants selected for an investigation are assigned to a treatment, control, or comparison group based on some randomizing technique.

This randomizing technique can be used for the lottery, use of a set of random numbers, or a systematic sampling technique.

A

Random assignment

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39
Q

Established treatment, control, or comparison groups are evaluated on the dependent variable prior to the introduction of any treatment.

A

Pretesting

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40
Q

Participants in the treatment, control, or comparison groups are matched on characteristics thought to be important to the D pendant variable.

A

Matching

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41
Q

All participants in all groups are kept uniform with regard to significant characteristics thought to influence the dependent variable

A

Constancy matching

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42
Q

Each participant in the treatment, control, or comparison group is matched with participants in the other groups, based on characteristics thought to influence the dependent variable

A

Pairing

43
Q

If the research setting has been created by the investigator, who maintains complete control over all that occurs in that setting, the study is known as a

A

Laboratory experiment

44
Q

The other setting is the naturally occurring research setting, where the investigator has no opportunity to shape the setting to his or her preference

A

Field experiment

45
Q

They examine only one independent variable at a time

A

Single-factor studies

46
Q

Many times, however, researchers choose to examine the influence of two or more independent variables, or factors, as they simultaneously influence a dependent variable.

A

Factorial studies

47
Q

3×2×3×2

A

36 cells

48
Q

Would most likely be used by our instructor in the sample scenario. In this design, a separate group of participants, or subjects, would be used in each of the cells so that comparison could be made between cells.

A

Between-subject design

49
Q

In some situations, the liability of the between-subject design can be alleviated by using the same subjects in each of the cells in the design diagram.

A

With in-subject design

50
Q

In those situations in which that within-subject design is impractical, but the number of subjects required for a between-subject design proves unrealistic, the researcher may combine the two approaches into a mixed factorial design. In this design, the same subjects are used across the levels of one or more independent variables, while a difference that is used across the levels of the remaining independent variables

A

Mixed factorial design

51
Q

Intervening variable

A

Bad, you control

52
Q

2×2×3 =

A

12

2 -independent variable, 2 -independent variable, 3 -independent variable.

2 - levels, 2 - levels, 3 - levels.

53
Q

Method that can even evaluate the casual relationship between the independent variable and the dependent variable while controlling for other intervening variables

A

Experiments

54
Q

A simple relationship between independent variable and Dependant variable

A

Correlation

55
Q

Goes one way

A

Casual relationship

56
Q

Temporal ordering-causes independent proceeds in effect Dependant in time.

Meaningful correlation-theory.

No alternative causes-no other explanation for the causes.

A

Three requirements of causality

57
Q

Alternative cause, other valuables that might influence or interfere the relationship between the independent and the Dependant variable

A

Intervening variables

58
Q

Most of the independent variables in experiments are manipulated by researchers

A

Manipulation

59
Q

Receive some level of treatment on independent variable

A

Treatment group

60
Q

Receives no treatment on independent variable

A

Control group

61
Q

Must ensure that groups are equivalent with regard to the Dependant variables before the treatment.

A

Group equivalence

62
Q

How can we check group equivalence?

A

Random assignment-it usually works. Can use statistical testing to doublecheck.

Pretesting-pretest (8), posttest (9), Treatment (post-pre-) versus control (post-pre)

63
Q

Participants in groups are matched on characteristics that are important to dependent variables

A

Matching

64
Q

Cannot manipulate independent variable

A

Comparison group

65
Q

Each participant in a group is mashed with another participant in another group. Gender gets balanced

A

Paring

66
Q

Two or more independent variables in the same argument

A

Factorial studies

67
Q

Different participants in each cell. Comparison between the cells

A

Between subject design

68
Q

Everyone goes through all, repeated measures

A

Within subject design

69
Q

Combination of the between and with in design

A

Mixed factorial design

70
Q

Surveys use self-report technique

A

Survey methods

71
Q

Advantages of survey methods

A

Access to subjective info. Access to broadly distributed population (email)

72
Q

Disadvantages of survey methods

A

Requires respondents to recall (people have to think). What participants report and actually do, could be different

73
Q

Survey designs

A 
Cross-sectional study
Longitudinal study
Trend study
Panel study.
CLTP
74
Q

One time data collection. (Once and done) response from a single point in time. Example = teacher semester evaluation’s.

A

Cross-sectional study

75
Q

Asking some questions across a period of time

A

Longitudinal study

76
Q

DIFFERENT samples from a population at different time points.

A

Trend study

Circle = population, little circle with in population (May, June, April)

77
Q

The SAME sample at different time points

A

Panel study

Circle = population, little circle within population (May, April, June, July)

78
Q

Panel study is highly vulnerable to several threats

A

Attrition (drop out)
Test sensitization
History
Maturation (tired, changing mind)

79
Q

Major sections of designing survey instrument

A

Introduction
Instructions
Questionnaires
At the end…

80
Q

Brief introduction of the study. (Researcher, purpose, etc.) participants rights-voluntary, right of withdrawal, ambiguous, confidentiality. Time required (10 to 15 minutes of your time)

A

Introduction

81
Q

Complete and concise set of instructions how to select items-only one? Multiple? Rank order?

A

Instructions

82
Q

Basic guideline = be clear, simple, understandable language, ninth grade level, be concise (simple to the point) lengthy, participants may skip them, be realistic

A

Questionnaires

83
Q

Add filter questions if necessary (do you use Twitter?)

A

Questionnaires

84
Q

Demographic information, write a thank you!

A

At the end

85
Q

How many hours of TV did you watch last year? = Bad, avoid bias wording-‘‘do you read newspapers or just watch TV?’’ (Take out word JUST), avoid leading questions-don’t you like our product? = Bad, avoid double barreled questions = asking a single question that ask for more than one response.

A

Things to avoid when designing surveys

87
Q

Accurate findings about the phenomena under investigation for the particular groups of people studied.

A

Internal validity

88
Q

Events which occurred during the study, influence participants behavior with in the study. Changes in the environment.

A

History

89
Q

And initial measurement in a research study influences the subsequent measurement. Pretest affects posttest.

A

Test sensitization

90
Q

Instruments wearout (out of date)

A

Instrument Decay

91
Q

Subjects change their behavior because they know that they are being observed.

A

Hawthorne effect

92
Q

Participants are being self-selected because people are self-selected, the study may not be good to represent the whole population. Could occur during the recruitment process.

A

Self-selection Bias

93
Q

Natural changes that occur within participants over the course of the study. Tired, sick, bad day, sad, happy. Physiological/psychology.

A

Maturation

94
Q

Dropping out from the study. Lost interest, forgot, do not care.

A

Attrition/mortality

95
Q

Nonhuman elements. YouTube, blogs, websites.

A

Data

96
Q

Participants influence each other. Do not speak about what is going on in the study until it’s over.

A

Inter-participant bias

97
Q

Problems with researchers methodology

A

Personal attribute effect, research bias. PA, RB

98
Q

Personal attribute effect, research bias. PA, RB

A

Problems with researchers methodology

99
Q

Researchers characteristics influence participants behaviors. People may not be honest with you, your personality, outfit, ethnicity, gender.

A

Personal attribute effect

100
Q

Accidentally informs the participants of what he/she expects. Do not say anything about your data.

A

Researcher bias

101
Q

Type your pre-a validated questions and instructions.

A

Script

102
Q

Hire a researcher (or assistant) who can conduct the study. The hired person doesn’t need to know the hypothesis/research questions.

A

Double-blind study

103
Q

Relationship between sample and population. Population = college students, sample = group of people that represent population.

A

External validity

104
Q

The results of the study can be “generalizable” to population.

A

Good external validity

105
Q

Representation

A

Generalizable

106
Q

Generalizable

A

Representation

Old Degree Communication Research Methods (2 decks)

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