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Research Methods > Test #2 > Flashcards

Test #2 Flashcards

1
Q

Surveys and questionnaires are most commonly used in which type of method?

A

Quantitative

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2
Q

What are surveys/questionnaires used for?

A

Obtaining information about what people do, and respondent’s attitudes or characteristics.

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3
Q

What are surveys?

A

Conversations between the researcher and respondent. (One way communication)

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4
Q

Ways to collect survey info:

A 
Paper/pencil
Face-to-face
Phone
Mail
Computer assisted
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5
Q

What are the benefits of computer assisted surveys?

A

Less time
Cost effective
Wide reaching
Reduces human error

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6
Q

Where should demographics (sex, age, income) be on a survey?

A

At the end

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7
Q

Respondents use their own words to respond.

A

Open questions

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8
Q

What must the researcher do after all data are collected?

A

Code responses

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9
Q

Respondents given a question or statement and given a set of responses to select from.

A

Closed questions

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10
Q

What kind of scale is this?

Please indicate your attitude toward blank
Highly undesirable—————-highly desirable

A

Graphic rating scale

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11
Q

What is a benefit of the graphic rating scale?

A

Sensitive system that required measuring actual physical distance on the line for dating coding.

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12
Q

What is a disadvantage of the graphic rating scale?

A

Significant amount of time and labor.

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13
Q

When is a graphic rating scale practical and useful?

A

During online surveys

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14
Q

What kind of scale is this?

Please indicate your attitude toward…
(1). (2). (3). (4). (5).
Highly undesirable. Highly desirable

A

Itemized rating scale

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15
Q

Benefits of itemized rating scale

A

Easier to respond and code data

More practical than a graphic scale

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16
Q

Disadvantages of an itemized rating scale?

A

Lack of sensitivity

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17
Q

What kind of scale is this?

Highly undesirable Desirable Highly desirable

A

Combination of graphic and itemized

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18
Q

Question contains several issues in one question but only provides one set of responses.

Ex. Do you think there is too much sex and violence in today’s media?

A

Double barreled questions

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19
Q

Questions presenting only one aspect of an issue on which respondent’s reactions are being sought.

Ex. Do you think the mad media are negatively influencing individuals mental health?

(Yes). (No)

A

One sided question

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20
Q

What is the problem with one sided questions?

A

People tend to agree with whichever side is presented.

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21
Q

Steer respondents toward a certain answer.

Ex. Don’t you think driving a SUV is harmful to the environment?

A

Leading questions.

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22
Q

A 7 point scale is always better than a five point scale. True or false?

A

True

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23
Q

Usually consists of multiple items and 5 choice categories in each question. (Multi dimensional variable)

A

Likert scale

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24
Q

Also called cross sectional or non experimental studies. Common, quick, and easy form of research.

A

Descriptive design

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25
Q

What can descriptive design not determine?

A

Causal relation. (No manipulation of the IV)

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26
Q

There is no what in descriptive design?

A

Condition

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27
Q

What are surveys useful/not useful for?

A

Useful for detecting differences/relationships. Not useful for finding cause and effect

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28
Q

Used to determine causation. (Conducted in a lab or controlled setting)

A

Experimental designs

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29
Q

Why are experimental designs set in a lab?

A

To control extraneous influences.

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30
Q

What are extraneous influences also known as?

A

Confounding variables (weakens the relationship)

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31
Q

The independent variable is manipulated by the researcher during…

A

Experimental designs

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32
Q

3 Necessary conditions of causality

A
  1. Temporal ordering
  2. Evidence of association
  3. Control for other variables
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33
Q

Cause variable must occur before the effect variable

A

Temporal ordering

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34
Q

There must be a relationship between cause (IV) and effect (DV). Must be a covariance

A

Evidence of association

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35
Q

The causal variable must be manipulated while others are being controlled for

A

Control for other variables

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36
Q

Experiment done in artificial setting. High internal validity, low external validity

A

Lab experiment

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37
Q

Ability to determine whether the observer result (DV) is due solely to the manipulation (IV)

A

Internal validity

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38
Q

ability to generalize the research findings to the real world.

A

External validity

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39
Q

Done in the “real world” instead of a lab setting. High external validity, low internal validity

A

Field experiment

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40
Q

What can feed experiments be interfered by in Communication research?

A

Unexpected situations

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41
Q

Field experiments are popular in what?

A

Marketing

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42
Q

Specific external events that occur during experiment that can affect the dependent variable. (Ex. Temperature)

A

History effect

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43
Q

Effect of psychological/physiological changes among the participants during the course of the experiment.
Ex. Tiredness

A

Maturation effect

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44
Q

The result of post-manipulation test is being affected by the pretest conducted previously.

A

Pretesting effect

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45
Q

Effects of inconsistent or inaccurate instruments used between pre testing and post testing.

A

Instrument variation effect

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46
Q

Effects of selecting non equivalent samples between control and experimental.

A

Selection bias effect

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47
Q

What are the 5 threats to internal validity?

A
  1. History effect
  2. Maturation effect
  3. Pretesting effect
  4. Instrument variation effect
  5. Selection bias effect
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48
Q

What are the 3 threats to external validity?

A
  1. Reactive bias
  2. Pretest (manipulation interaction bias)
  3. Jon representative sampling bias
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49
Q

Effects of participants reacting to the experimental environment, causing them to exhibit abnormal behavior.

A

Reactive bias

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50
Q

Effects participants becoming more or less sensitive to the manipulation variable due to pretesting measurement.

A

Pretest (manipulation interaction bias)

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51
Q

Effects of selecting participant samples that do not represent the targeted population.

A

Nonrepresentative sampling bias

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52
Q
  1. Little or no control over confounding variables.
  2. Participants are not randomly assigned to a condition
  3. Still, often used as a basis of causal inferences because of practical reasons
A

Quasi-experimental design

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53
Q
  1. Tighter control over validity issues
  2. Utilize experimental and control groups
  3. Utilized random assignments to create equivalent groups.
  4. Sometimes matching, or matching random assignment can be used to create equivalent groups.
A

True (classical) experimental design

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54
Q

What is the most complete and true experimental design?

A

Solomon’s 4 group design

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55
Q

Solomons 4 group design has

A

No inherent threat to validity at all

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56
Q

What are the pitfalls of solomons 4 group design?

A

Cost/time inefficient

Almost impossible to implement in the real world.

57
Q

Treatment of groups based on two or more levels of independent variables. (More than one cause)

A

Factorial experimental design

58
Q

When is the dependent variable measured in the factorial experimental design?

A

Once after treatment is given.

59
Q

What can factorial experimental design test for?

A

Main and interaction effects

60
Q

Multiple measurements of the dependent variable across time. (Long-term effects)

A

Longitudinal experimental design

61
Q

What is the threat to longitudinal experimental design?

A

Losing participants over time which can make the conclusion weak

62
Q

What do numbers collect?

A

Data, phenomenon, quality, intensity, value, or degree

63
Q

Specifies how data are collected and become numerical.

A

Operationalizations

64
Q

A theoretical distribution of scores. Also know as the bell curve.

A

Normal curve

65
Q

Normal curves are what?

A

Symmetrical

66
Q

Mean median and mode are identical

A

Normal curve

67
Q

Majority of cases distributed around the peak in the middle in what curve?

A

Normal curve

68
Q

Curve is asymmetrical

A

Skewed distributions

69
Q

Very few high scores

A

Positively skewed

70
Q

Very few low scores

A

Negatively skewed

71
Q

When mean is the lowest…

A

Negatively skewed pattern. Caused by low outliers

72
Q

When mean score is the largest…

A

positively skewed pattern. Caused by high outliers

73
Q

Central tendency is what?

A

Mean, median, more

74
Q

How much subjects differ from group mean

A

Dispersion or standard deviation.

75
Q

Number of cases are represented by what?

A

N

76
Q

What are the 3 types of descriptive stats?

A
  1. Number of cases
  2. Central tendency
  3. Dispersion
77
Q

Dispersion describes what?

A

The variability or spread of scores.

78
Q

If sd equals zero…

A

All scores are the same

79
Q

The larger the sd…

A

The more scores differ from the mean

80
Q

Standard deviation estimates what?

A

Sampling error

81
Q

Sd determines the?

A

Set range

82
Q

For the data to be considered a normal distribution, it must be?

A
  1. Identical mean, median, and life

2. Data must be within set range

83
Q

Theoretical normal curve should be divided into?

A

Equal standards

84
Q

If the distribution is perfectly normal, what percent of the data should fall within the +1 to -1 range?

A

68.26%

85
Q

Standard deviation must be?

A

Positive

86
Q

What does it mean if the distribution is not perfectly normal?

A

There is sampling error

87
Q

Often used to describe characteristics or attributes of participants

A

Percentages

88
Q

Reveal whether the observed differences that might occur by chance

A

Statistical tests of difference

89
Q

What are the statistical tests of difference?

A

Chi square
T test
ANOVA

90
Q

Statistical test used to evaluate hypothesis and research questions

A

Inferential statistics

91
Q

If results are statistically significant then?

A

Results are assumed to hold true for the population.

92
Q

What do inferential stats test?

A

The likelihood that the alternative hypothesis is true and the null isn’t.

93
Q

What is generally considered statistically significant ?

A

.05

94
Q

If p< or equal to 0.5…

A

Alternative hypothesis is accepted

95
Q

If p> .05…

A

Null hypothesis remains

96
Q

Specifies how many values vary within a statistical test.

A

Degrees of freedom (df)

97
Q

Compares the observed frequency with the expected (hypothetical value when everything is equal) frequency

A

Chi square

98
Q

Degree must be what for both IV and DV in chi square?

A

Nominal or categorical

99
Q

Total sample size divided by number of categories.

A

Expected frequency

100
Q

What is the df in chi square?

A

Total number of categories minus 1

101
Q

What must the measured value be, to be significant?

A

Greater than or equal to the critical value

102
Q

Determines if differences in how cases are distributed across categories of one nominal variable are significant.

A

One dimensional chi square

103
Q

What does significant chi square indicate?

A

Variation of frequency across categories did not occur by chance

104
Q

What are the limitations of chi square?

A
  1. Only use nominal data variables
  2. Tests may not be accurate if observed frequency is zero or less than 5.
  3. Cannot directly determine causal relationships.
105
Q

Represented by t

A

T test

106
Q

Determines if differences between two groups of the independent variable on the dependent variable are significant.

A

T test

107
Q

In the t test, the IV must be

A

Nominal data of two categories

108
Q

In the t test, the DV must be

A

continuous level data at interval or ratio level

109
Q

Compares mean scores from IV for two groups of people.

Ex. Difference between males and females on aggression after playing violent video games

A

Independent sample t test

110
Q

Compares mean scores of paired or matched scores from IV from the same participants.

Ex. Difference in aggression between before and after playing video games from males

A

Paired comparison t test

111
Q

Hypothesis or research question indicates that a difference in either direction is acceptable

A

Two tailed or non directional t test

112
Q

Hypothesis or research question that specifies the difference to be found.

A

One tailed or directional t test

113
Q

What are the limitations of t test?

A
  1. Limited to differences of two groupings of one IV on a DV

2. Cannot examine complex communication phenomenon

114
Q

Compares the influence of more than two groupings of IV on the DV. Represented by f

A

Analysis of Variance (ANOVA)

115
Q

In ANOVA, the IV must be

A

Nominal

116
Q

In ANOVA, the DV must be

A

Continuous level data

117
Q

What types of variances does ANOVA look at?

A

Between group and within group

118
Q

Differences between groupings of IV are large enough to distinguish themselves from one another.

A

Between group variances

119
Q

Variation among individuals within any category or grouping. (About average)

A

Within group variance

120
Q

The better the categories of the IV explain variation in the DV, the larger the…

A

F

121
Q

Tests for significant differences in the DV based on categorical differences of one IV

A

One way ANOVA

122
Q

Difference between groups is larger than difference within groups.

A

Significant f

123
Q

Determines relative contributions of each IV to the distribution of the DV

A

Two way ANOVA

124
Q

What can two way ANOVA determine?

A

The main effect of each IV and the interaction effect

125
Q

If there is a simultaneous influence on both IVs

A

Interaction effect

126
Q

If interaction effect exists, then the main effect…

A

Is ignored

127
Q

What are the limitations of ANOVA?

A

Restricted to testing IV of nominal or categorical data, and can be difficult to interpret when 3 or more IVS are used.

128
Q

2 continuous level variables

A

Correlation

129
Q

Identified statistically significant linear patterns in the association of variables.

A

Tests of linear relationships

130
Q

In inferential stats, both variables must be what for correlation?

A

Interval or ratio

131
Q

If r value is closer to zero, the relationship is…

A

Weaker

132
Q

What can r value determine?

A

The strength of the relationship

133
Q

R = 0 means that…

A

There is no relationship

134
Q

Correlation reveals one of the following:

A
  1. Scores on both variables increase or decrease together
  2. Scores on one variable increase (or decrease) scores on the other variable decrease (or increase)
  3. No pattern or relationship.
135
Q

What does r reveal?

A

The degree to which two continuous level variables are related.

136
Q

It r is found with p that is less than or equal to o.5, then the relationship is

A

Significant

137
Q

Both variables increase or both decrease

A

Positive correlation

138
Q

One variable increases while the other decreases

A

Negative correlation

139
Q

Limitations of correlation

A
  1. Can only examine the relationship between two variables at a time.
  2. Any relationship is presumed to be linear.
  3. Limited in the degree to which inferences can be made.

Research Methods (3 decks)

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