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PSYC 277 > Midterm 1 Psyc 277 > Flashcards

Midterm 1 Psyc 277 Flashcards

1
Q

Illusory correlation

A

A cognitive bus that occurs when we focus on two events that stand out and occur together then make a conclusion after that.

Ex: conclusion that when you’re not looking for bf you get a bf

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2
Q

Authority

A

We place our trust in someone who we think knows more than we do.

Ex: we always believe what doctors or profs say

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3
Q

Scientific skepticism

A

Recognizing that our own ideas are just as likely to be as wrong as someone else’s and questioning other people’s opinions on what is true, regardless of their prestige or authority.

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4
Q

Empiricism

A

Fundamental characteristic of the scientific method. Knowledge is based on structured systematic observations

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5
Q

What are the 4 norms that characterize scientific inquiry

A

1- universalism
2- communality - methods and results are to be shared openly so study can be replicated. Meta-analysis studies that combine results from many studies
3-disinterestedness - see if other theories or experiments prove their hypothesis wrong
4- organized skepticism - peer review

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6
Q

Falsifiable

A

If an idea is falsifiable it can either be supported or refuted using empirical data. And you can conduct studies to test it.

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7
Q

Pseudoscience

A

Using scientific terms to make a claim look compelling but without using actual scientific data

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8
Q

4 goals of scientific research in psychology:

A
  1. To describe behaviour
  2. To predict behaviour
  3. To determine causes of behaviour
  4. To understand or explain behaviour
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9
Q

Describing behaviour

A

Involves careful observation and measurement

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10
Q

Predicting behaviour

A

Predictions based on observation from prior behaviour or studies.

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11
Q

Determining causes of behaviour

A

Making causal claims.

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12
Q

Criteria for causal claims (cause and effect) (determining causes of behaviour):

A
  1. Covariation of cause and effect: when the cause is present the effect occurs, when it’s not the effect doesn’t occur
  2. Temporal precedence: cause precedes effect
  3. Elimination of alternative explanations: nothing other than the causal variable could be responsible for the observed effect.
    •There shouldn’t be alternative explanations for
    the relationship
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13
Q

Explaining behaviour

A

Why events and behaviour occur.

Why there may be a correlation between variables.

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14
Q

Basic research

A

Attempts to answer fundamental questions about the nature of behaviour.

Studies often designed to develop and test aspects of theories about certain phenomena such as cognition, emotion, motivation, learning, personality, psychobiology and social behaviour.

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15
Q

Applied research

A

Conducted to address practical problems and possible solutions.

Some offer insight into problems or solutions
Some offer specific tools to address those problems in specific settings

Major area of applied research is Program Evaluation:- Which tests their efficacy of social reforms and innovations that occur in governments, education, criminal justice systems, industry, health care institutions.
- used to determine how effective these programs are.

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16
Q

How are applied research and basic research integrated?

A

Finishing a obtained in applied research often suggest modifications of existing theories and so lead to more basic research.

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17
Q

How are common assumptions important?

A

Testing common assumptions by using scientific research can lead to valuable findings.

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18
Q

How is the “Observation of the world around us” a source of research ideas?

A

Observation of personal and social events can lead is to develop intuitions about the world. We can then push these intuitions to file research.

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19
Q

Practical Problems

A

The purpose of applied research is to address practical problems directly.

Ex: how do we get people to stop smoking? -> development of graphic warming labels on cigarette boxes by applied research seemed to decrease smoking.

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20
Q

Theory

A

A system of logical ideas that are used to explain a particular phenomenon and it’s relationship to other phenomena.

  • theories organize and explain a variety of specific facts or descriptions of behaviour. It also helps explain actual data from prior research
  • theories generate new knowledge by focusing our thinking so that we notice new aspects of behaviour. Therefore they bring upon new hypotheses that can be tested to further support or reject the theory or modify theory.
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21
Q

If multiple theories are equally successful at explaining the same phenomenon, how do we determine which one is the best one?

A

the scientific principle of Parsimony: dictates the least complex theory is most desirable, because it’s easiest to falsify.

The theory with the least variables is best.

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22
Q

How can past research be one of the best ways of generating new ideas for research?

A
  • you can find inconsistencies in the results of past research, which may lead you to conduct ur own research.
  • you may propose a new theory that can also explain their existing results
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23
Q

What are the 6 major sections of a research article?

A
  • abstract
  • introduction
  • methods
  • results
  • discussion
  • references
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24
Q

Abstract

A

Summary of the research report.
120 word or more.
Includes hypothesis, info about procedure, and info about results

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25
Q

Introduction

A
  • outline problem being investigated
  • past theories and research related to problem
  • the gap that exists in prior research
  • current study is introduced to fill the gap
  • ends with hypothesis and research question
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26
Q

What are the subsections of the methods part in an article?

A
  • participants’ characteristics
  • procedure
  • equipment/ testing materials
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27
Q

What are the people who take surveys called ?

A

Respondents

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28
Q

What do u call those who give info about a culture on an organization to the researcher ?

A

Informants

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29
Q

Discussion

A

Research reviews the current study from many perspectives.

  • it explains results and whether they support hypothesis
  • errors and their sources
  • comparison to other studies
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30
Q

Citations

A

Names and dates at the end of some sentences

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31
Q

Literature review Articles

A

Articles that use narrative techniques.

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32
Q

Meta-analysis articles

A

Articles that use statistical techniques

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33
Q

Best online data baases for PSyc research

A

PSyc info and google scholar

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34
Q

Name 2 major psychology journals:

A
  • American Psychologist

- British journal of psychology

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35
Q

Research Hypothesis

A

Is a statement about something that may or may not be true, is informed by past research or derived from a broader theory, and is waiting for evidence to support or refute it

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36
Q

If no research has been done before I a particular subject or idea, researchers can take this approach:

A

Exploratory research that’s not aimed to test a hypothesis.

*new experimental data doesn’t necessarily have to be included in this type of research

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37
Q

Prediction

A

After designing the study, the researcher would turn his general hypothesis into a prediction concerning the outcome of the particular experiment. Predictions are more specific than hypothesis.

PREDICTIONS ARE IN FUTURE TENSE, HYPOTHESIS IS IN PRESENT TENSE

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38
Q

Examples of Infaulsifiable stuff

A

Religion

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39
Q

What makes a hypothesis scientifically meaningful?

A

Falsifiability

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40
Q

Variables

A

Any event, situation, behaviour, or individual characteristic that can take more than one value.
*at least 2 specific levels of value

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41
Q

Non-experimental method

A

Relationships are studied by observing or otherwise measuring the variables of interest.

  • both variables are measured when using the non-experimental method.
  • asking people to describe their behaviour
  • directly observing behaviours - ex in a bad
  • recording physiological responses
  • examining public records like cences
  • researcher uses statistics to determine whether there is a relationship between variables. Ex- correlation
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42
Q

Experimental method

A

Involves direct manipulation and control of variables

- the researcher manipulated the first variable of interest and then observed the response

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43
Q

Operational definition

A

A definition of the variable in terms of the operations or techniques used to measure or manipulate it

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44
Q

Situational variable

A

Describes characteristic of a situation or environment.
- can be be measured in any design or manipulated in experimental design

EX: number of people in a classroom, credibility of a person, number of bystanders in an emergency.

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45
Q

Response variable

A

Responses or behaviours of individuals, such as reaction time, performance on a cognitive tasks, or degree of helping in an emergency for each person.

*measures in either experimental or non-experimental design

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46
Q

Confounding variables

A

Variables that are inter winded with another variable so that you cannot determine which of the variables is pertains in a given situation.

  • they impede our ability to make claims
  • can occur in research because of imprecise operational definitions
  • can occur if independent variable is manipulated imprecisely
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47
Q

4 types of correlation relationships between variables in non experimental design:

A
  • Positive linear relationship
  • negative linear relationship
  • curvilinear relationship ( increases in value of one variable are accompanied by both increases and decreases in the values of the other variable)
  • no relationship (Horizontal line)
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48
Q

Correlation coefficient

A

A numerical index of the strength of relationship between variables

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49
Q

Mediating variable.

Provide an example:

A

A psychological process that occurs between two variables that helps to explain the relationship between them.

Ex:
Claim: the more that children were unable to keep focused attention, the more problems they had relating to their peers.

  • the more inattentive the children were, the less the showed prosocial concern for their peers and the more the behaviour problems they had, which then both related to more peer problems.
  • Mediating variables: prosocial concern and behaviour problems mediated the relationship between inattention and peer problems
  • Can also be considered participant variables
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50
Q

Uncertainty / error variability

Define and explain how it can be reduced.

A

Randomness of events in an experiment.

Research is aimed at reducing error variability by identifying systematic relationships between variables.
- one way is by conducting further research you can reduce error variability and identify other variables that are related.

Ex: Facebook use correlates to narcissism

  • further research can be done to find other variables related, like slow self-Esteem.

This additional variable lab a way to decrease error variability / uncertainty.

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51
Q

There are two problems preventing researchers from making causal statements in non-experimental methods:

A
  1. It can be difficult to determine the direction of cause and effect
  2. The third-variable problem: which are extraneous variables that can be causing the observed relationship
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52
Q

Third variable problem

A

A relationship between two variables may occur in a study because some other variables that were not measured causes both exercise and happiness for example.

  • any number of other third variables may be responsible for an observed correlation between two variables.
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53
Q

Claim: Data may show a negative correlation between increase of alcohol consumption per week and getting lower grades in school.

What are possible confounding variables?
What are possible third-variables?

A

Possible third-variables: poor decision-making skills might cause people to drink more alcohol while simultaneously causing them to have low grades.

Possible confounding variable: if people who drink more alcohol are also more socially active than people who drink less alcohol. Then time spent socializing is confounded with alcohol consumption.

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54
Q

What is the difference between third-variables and confounding variables?

A

Third variables cause the apparent relationship between two other variables, whereas, confounding variables are inter winded with another variable in your study so that you cannot tell which is at work.

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55
Q

Independent variable

A

“The cause”, manipulated variable,

Horizontal axis

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56
Q

Dependent variable

A

“The effect”, measured variable, vertical (y) axis.

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57
Q

Internal validity

A

The ability to draw accurate conclusions about causal relationships from our data.

When researcher designs a study that effectively meets all 3 criteria for cause and effect —> this has high internal validity

  • internal validity is achieved in experiments also by using random assignment and ensuring that only the independent variable of interest changes across conditions.
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58
Q

Experimental control

A

Treat participants in all groups in the experiment the same so that the only difference between groups is the independent variable.

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59
Q

Random assignment

A

Ensures that extraneous variables are just as likely to affect one experimental group as they are to affect the other group, as long as there are enough participants in the study.

Random assignment can also be used to assign random times to the participants to come in and do the study.

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60
Q

Cause and-effect relationship is established only if the cause is both necessary and sufficient for the effect to occur.

True or false

A

True

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61
Q

Issue of the artificiality of experiment:

A

The high degree of control and laboratory setting can sometimes create an artificial atmosphere that may limit either the questions being addressed or the generality of the results.

Adding non experimental studies like field study can help address these concerns.

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62
Q

How are non-experimental studies sometimes more important for experiments describing behaviour?

A

When the research goal is to describe events accurately, causal claims are irrelevant, and therefore, experiments are unnecessary.

Ex: describing children’s behaviours as they gradually develop.

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63
Q

Reliability (precision)

A

Consistency or stability of a measure of behaviour.

Operational definitions need to have high reliability

Increasing reliability decreases uncertainty.

Taking multiple measures of a variable increases reliability and decreases uncertainties.

Ex: a personality test that gives you the same results every time you take it within a month is reliable.

Random error and noise reduces reliability of measures.

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64
Q

True score

A

A person’s true score on the variable.

A reliable measure has little to no measurement error and so provides the true score.

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65
Q

Pearson product moment correlation coefficient

A

The most common correlation coefficient when discussing reliability of measure.

Symbol r

Can range from 0.00 to+1.00 and 0.00 to -1.00

R = 0.00 Measure not related to variable at all

The closer r is to +1 or -1 the stronger the relationship

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66
Q

Test-retest reliability

Alternate forms reliability

A

Assessed by giving many people the same measure twice.
Ex: by giving intelligence test twice on different weeks to assess reliability of test based on similarity of results.

Reliability coefficient for most measures should be at least r = 0.80

Alternate forms reliability: is used to avoid that people may remember test answers the following week. It involves two different forms of the same test.

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67
Q

Internal consistency reliability

A

Assesses how well a certain set of items relate to each other.
Because all items measure the same variable, they’d Gould yield similar or consistent results

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68
Q

Cronbach’s Alpha

A

One common indicator of internal consistency. I’m this analysis the researcher calculates how well each item correlates with every other item, which produces a large number of inter item correlation.

The value of Cronbach’s alpha is based on the average of all the inter-item correlations and the number of items in the measure.

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69
Q

Interrator reliability

A

The extent two which eaters agree in their observations

High interrator reliability is obtained when most of the observations of the two individuals (raters) result in the same judgement.

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70
Q

Cohen’s Kappa

A

Common indicator of interrator reliability

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71
Q

Validity (accuracy)

A

The adequacy of a variable’s operational definition. The degree to which the operational definition of a variable actually reflects the true theoretical meaning of the variable.

Whether measure that is employed actually measures what it’s supposed to measure.

Ex: LSATs are considered to be a valid measure of preparedness for law school.

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72
Q

Face validity

A

To suggest that the measure appears to accurately assess the intended variable and therefore is valid.

Face validity is an inaccurate method of measuring validity. It’s just what “looks” valid may not be actually a valid measure.

73
Q

Content validity

A

Is based on comparing the content of the measure with the theoretical definition of the construct

Doesn’t work well

Researchers disagree on the theoretical definitions of constructs

74
Q

Predictive validity

A

Using the measure to predict some future behaviour.

75
Q

Concurrent validity

A

Is assessed by research that examines the relationship between the measure and a criterion behaviour at the same time.

  • a common method is to study whether two or more groups of people differ on the measure in expected ways. (Eg. people who plagiarized and people who didn’t plagiarize)

Ex: psychopathy scale identified more psychopathic tendencies among university students who plagiarized on essays than among those who did not plagiarize on essays. The score effectively distinguished people who acted unethically from people who did not, thereby demonstrating concurrent validity.

  • another approach to concurrent validity is to study how people who score either high or low on the measure behave in different situations
76
Q

Convergent validity

A

Is the extent of how scores of one operational definition relate to scores from another operational definition of the same construct or different constructs.

Measures of similar constructs should “converge”

77
Q

Descriminant validity

A

When the measure is not related to variables with which it should not be related, discriminant validity is demonstrated.

78
Q

Reactivity

A

Awareness of being measured changes individual’s behaviour

79
Q

Nominal

A

Categories with no numeric scales.

Ex: females / males

80
Q

Ordinal

A

Rank ordering. Numeric values have limited meaning.

Ex: gold, silver, bronze
1 , 2, 3, 4 star restaurant

Intervals between items are not known and inconsistent.

81
Q

Interval

A

Numeric properties are literal. Assume equal interval between values.

Ex: intelligence score, temperature

  • distinction: no true zero, value is never absent
82
Q

Ratio

A

Zero indicates absence of variable.
Assume equal interval between values
Ex: reaction time, age, frequencies of behaviour, weight.

Destination - can form ratios (eg someone responds twice as fast as another person)

83
Q

Subtraction rest

Midway test

A

Use subtraction test to distinguish between quantitative or categorical values.

Use midway test to distinguish between discrete or continuous.

84
Q

Frequency distribution

A

Indicates the number of participants who receive or select each possible score on a variable and can be created for variables using any scales.

85
Q

Outliers

A

Scores that are unusual.

86
Q

Histograms

A

Uses bars to display a frequency for a continuous variable.
X axis can contain values like blood pressure, reaction time, number of correct responses, etc.

Bar graphs are for discrete info.

87
Q

Frequency polygon

A

Alternative to histograms. Uses a line to represent frequencies when the variable uses an interval or ratio scale.

Helpful for examining frequencies for multiple groups simultaneously. Helps you see differences.

88
Q

Descriptive statistics

A

Calculated to make precise statements to summarize the data

89
Q

Central tendency

A

Describes the samples mean, median, and or mode

90
Q

Mean

A

Average. Symbol x with a line on top.

91
Q

Median

A

The score that divides the group in half. Important for ordinal scales.

92
Q

Mode

A

Most frequent score. Only measure appropriate for a nominal scale.

Less accurate tan mean and median in describing central tendency.

93
Q

Variability

A

The number that characterizes the amount of spread in a distribution of scores that are measured on interval or ratio scales.

Can be measured by standard deviation.

94
Q

Standard deviation

A

Symbol S.
Indicates how far away scores tend to be from the mean, on average.

Symbolizes as SD in reports.

SD is first derived by calculating variance which is S^2.

SD is appropriate only for interval and ratio scale variables.

95
Q

Range

A

Difference between highest score and lowest score.

Is a measure of variability.

96
Q

Graphing Nominal Data

A

By using bar graph or line graph.
Bar graph is used when values of x-axis are nominal.

Line graph is used when values on x axis are numeric

97
Q

Effect size

A

The extent to which our study’s results are meaningful. Describing relationships among variables in terms of size amount or strength.

98
Q

Survey research

A

Uses questionnaires.

99
Q

Closed-ended data

A

Numerical, nominal responses.

100
Q

Panel survey

A

When the same people are tracked and surveyed at two or more points in time.

“Two-wave” panel study: people are surveyed 2 times at different points of time.

“Three-wave” panel study- people surveyed 3 times….

101
Q

Response set

A

Is a tendency to respond to all questions from a particular perspective rather than to provide answers that are directly related to the questions.

102
Q

Social desirability response set

A

Participants respond in most socially acceptable way.

103
Q

What are the 3 general types of surveying questions?

A
  1. Attitudes and beliefs: how people feel about and evaluate certain issues
  2. Facts and demographics: factual questions ask people to indicate things they know about themselves and their situation.
  3. Behaviours: past behaviours or intended future behaviours
104
Q

What are common problems in the wording of survey questions?

A
  • unfamiliar technical terms
  • vague or imprecise terms
  • ungrammatical sentence structure
  • phrasing that overloads working memory
  • misleading info in question
105
Q

Unnecessary complexity

A

Is a problem that could occur in survey questions. Questions should be straight forward and no scientific jargon should be used.

106
Q

Double-barrel questions

A

Questions that ask two things at once. This can be confusing in surveys.

107
Q

Loaded questions

A

A question written to lead people or unintentionally convince them to respond in a specific way.

108
Q

Negative wording

A

Using “not” in survey questions for example. Negative wording causes confusing in survey questions, avoid using them.

109
Q

“Yes-saying” and “Nay-saying”

A

When you ask too many questions in a survey that require yes/no responses, responder mace have the tendency to either always says or always so no.
(Yes-saying or nay-saying response set)

110
Q

Rating scales

A

For closed ended questions, they ask people to rate how they are feeling, agree or disagree, etc.

111
Q

Labelling response alternatives

A

Fully labelled scales are more reliable.
Ex: if you ask the responder to date how well they felt on a scale of 1-10, try to explain what each number means in terms of feeling. (Sad, happy, really happy)

112
Q

What is the common number of response alternatives In Rating scales?

A

Researchers usually use a 5-point or 7-point scale, allowing there to be a middle that is “neutral”.

-sometimes users pick “neutral” when they don’t understand -> this decreases reliability and validity.

113
Q

High frequency scale vs low frequency scale:

A 
High frequency options:
Less than twice a week 
About twice a week
About 4 times a week
About 6 times a week
Low frequency options:
Less than twice a week
About once a month
About once every two weeks
More than once a week
114
Q

Graphic rating scale

A

Requires a mark along a continuous 100 mm line that can be placed by the participant on whatever position on the line.
There are descriptions on both ends.

115
Q

Semantics differential scale

A

Is a way to measure the measuring that people ascribe to concepts.

Ex: Using multiple adjacent pairs can help measure different aspects of attitudes towards smoking:
Good __ ___ ___ ___ ___ Bad
Strong ___ _ _ ___ __ weak
Active ___________ passive

Semantic scales are rated along 3 basic dimensions:

  1. Evaluation (good-bad)
  2. Activity (active-passive)
  3. Potency (weak-strong)
116
Q

Non-verbal scale

A

Using images or symbols. For kids for example.

Ex: using 😔😟😕😐🙂😊

117
Q

Formatting questionnaires

A

Make it look nice
Put interesting questions in the beginning
Make questions short

118
Q

Refining questions

A

Before survey, ask people to come and see what they think of ur questions to see if there’s anything u should change.

119
Q

Describe the survey method: Personal Administration To Groups of individuals

A

Researchers are able to give a survey to a whole class or at a work place. This approach involves a captive audience, researcher is also there to answer questions.

120
Q

What are the pros and cons of conducting a survey using an in person interview ?

A

Pros:

  • people feel more compelled to answer a real person than a computer.
  • interviewer motivates person to answer all questions, rather than leave them blank like they would do online or on paper.
  • you can ask interviewer questions

Cons:

  • interviewer bias: interviewer can influence answers by unconsciously looking more agreeable or disagreeable.
  • interviewer can also be biased or racist.
121
Q

What are the 3 methods of conducting an interview?

A

Face to face, telephone, and focus groups

122
Q

Focus groups

A

An interview with about a group of 7 to 10 people for 2-3 hours.
Questions are open ended

123
Q

Population

A

A set of people of interest to the research

124
Q

Sampling

A

Getting a smaller sample of the population and using the info of their characteristics to estimate the characteristics of the entire population.

125
Q

Confidence interval

A

A range of plausible values for the population value; values outside the confidence interval are implausible. The confidence interval gives you information about the likely amount of the error; for every 20 confidence intervals calculated, 19 will include the true value for the population, but one will not.

126
Q

Sampling error

A

The error that exists in the estimate because only a sample and not the entire population was measured

127
Q

External validity

A

Achieving external validity means that the sample is highly representative of the population from which it is drawn.

To achieve an unbiased sample you need to do random sampling.

128
Q

Sampling frame

A

The actual population of people from which the random sample will be drawn.

129
Q

Probability sampling

A

Each member of the population has a specific level probability of being chosen.

130
Q

Non-probability sampling

A

We don’t know the probability of any particular member of population being chosen.

131
Q

List the different types of probability sampling and non-probability sampling.

A

Probability:

  • simple random sampling
  • stratified random sampling
  • cluster sampling

Non-probability sampling:

  • convenience sampling
  • purposive sampling
  • quota sampling
132
Q

Simple random sampling

A

Every member of the population has an equal chance of being chosen.

Resulting sample is called a random sample.

133
Q

Stratified random sampling

A

Population is divided into subgroups (strata) and then simple random sampling is used to select sample members from each stratum.
Stratus may co rain different sexes, age groups, sexual orientation, amount of education, or different ethnicities.

134
Q

Cluster sampling

A

Rather than randomly sampling from a list of people, the researcher can identify “clusters” of people and then sample from these clusters.

Ex: ex sampling people from a cluster of students in a university classrooms.

135
Q

Convenience sampling

A

Participants are recruited wherever u find them.
Likely to introduce biases into the sample.
Limit you from having an accurate representation of the population.

136
Q

Purposive sampling

A

The purpose is to obtain a sample of people who meet some predetermined criterion.

  • ex: age, sex, etc.
  • sample is picked from people walking by for example.
  • limits conclusions
137
Q

Quota sampling

A

(Non-probability)

Researcher chooses a sample that reflects the numerical composition of various subgroups in the population.
- you will still collect ur data using convenience techniques.

138
Q

What is the first step of an experiment in detail?

A

Decide how to assign participants to the levels of the independent variable.

139
Q

Selection differences

A

Procedure must eliminate selection differences. The people selected to be in the conditions should not differ in any systematic way.
Ex: you can’t assign only rich people in the control group.

140
Q

Methods of assigning participants to experimental conditions:

A
  • Independent Groups Design:
    Randomly assign to only one level of the independent variable
  • repeated measures design: assign to all levels of the independent variable.
  • matched pairs design: first match each pair on a characteristic and the randomly assign one of each pair ONLY to one level of the independent variable.
    - this pair is a pair that scored similarly on some variable of interest.
141
Q

What is the second step of the experimental design in detail?

A

Operationally define the independent variable, creating at least two levels. Ex: one level receives treatment and one does not.

142
Q

What is the 3rd step of an experimental design in detail?

A

Determine a way to measure the effect of the independent variable by operationally defining the dependent variable.

143
Q

Independent group design (between-subjects design)

A

Where different participants are assigned to each level of the independent variable using random assignment.

  • you need a minimum of 30-50 participants per condition.
144
Q

Pre-test posttest Design

A

(part of independent group design) makes it possible for researchers to be sure that the groups were equivalent at the beginning of the experiment on a crucial variable. The two groups (experimental vs non-experimental) are given a pretest to compare them to ensure that they’re equivalent on that variable. (ex: equally smart)
- post test- refers to the dependent variable that is measure after the experimental manipulation.

145
Q

posttest-only design

A

when no pretest is given.

146
Q

what are the 3 main reasons to adda pre-test?

A

1) small sample size
2) to select appropriate participants
3) when participants might drop out of a study. (most likely to occur in a study that lasts over a long period of time).

147
Q

Mortality

A

The drop out factor in experiments. It’s a threat to internal validity.
pretest may be useful to see the effects and reasons of mortality.

148
Q

What is one problem of the pretest that may decrease validity of experiment? how can you try to solve this problem?

A

Pretest may make participants guess what the experiment actually is about, so, they’ll act differently (demand characteristic).
To solve this problem you can make the purpose of the experiment less obvious by adding deception and a bunch of irrelevant tests to confuse participants.

149
Q

solomon four group design

A

Add a pretest and no-pretest group. divide each group into the conditions (ex: experimental and control).
If there is no impact of the pretest, the average posttest results of the control groups will be the same.

150
Q

Repeated measures design

A

instead of random assignment to a condition, an alternative is to have the same individuals participate in all conditions.

151
Q

pros and cons of the repeated measures design:

A

Pros:

  1. less expensive
  2. less participants needed
  3. easier to run the experiment, takes less time and resources.
  4. extremely sensitive to detecting differences between levels of the independent variable. Eliminates individual differences of participants in the different experimental conditions.
    cons: Order effect: the order of presenting the treatments may affect the dependent variables.
152
Q

what are the different types of order effects? explain each one.

A

(in repeated measures design)

  • practice effect: performance improved because of repeated practice of task.
  • fatigue effect
  • contrast effects: occurs when response to the second condition in the experiment is altered because the two conditions are contrasted to one another.
153
Q

give an example of contrast effects in repeated measures design:

A

criminality study; first people read about murder then decide on a punishment. Then when they read about theft right after, they may give punishments that are a lot less harsh than they need to be. Therefore order was different and the results will likely be different.
order is confounded with crime severity.

154
Q

There are two ways to deal with order effects in repeated measures designs, what are they?

A

1) counterbalancing techniques

2) ensuring the time between conditions is long enough to minimize the influence of the first condition on the second.

155
Q

counterbalancing

A

all possible orders of presentation are included in the experiment. Half participants will be assigned to one order and half to the other order.

  • counter balancing can be extended to experiments with 3 levels or more
  • for 3 levels there are 6 possible orders, 3! = 3 x 2 x 1
  • for 4 levels there are, 4!= 4 x 3 x 2 X 1 = 24
156
Q

Partial counter balancing

A

To deal with 10! order for example, you cant do 3628800 orders. Latin square: is a limited set of orders constructed to ensure that 1) each condition appears at each ordinal position 2) each condition precedes and follows each condition once.

157
Q

If an experiment involves permanent changes, do you choose independent groups or repeated measures design?

A

Independent groups

158
Q

what is the next step after experiment/research design?

A

The next step is figuring out the operational definitions in details for each variable.

159
Q

straightforward manipulation

A

operationally define the independent variables using instructions and stimulus presentations.
stimuli may be presented verbally, in written form, via videotape or with a computer.
ex: showing participants a series of words and making them rate how much they liked each word.

160
Q

mundane realism

A

when tasks in a study mimic experiences and conditions present in every day life -> high mundane realism

161
Q

staged manipulations

A

Can be elaborate situations involving actors; at other times, they simply take the form of a cover story.
used for two reasons mainly:
1) researcher maybe trying to create some psychological state in the participants, such as frustration, or anger, or conformity.
2) to stimulate some situation that occurs in the real world.
- staged manipulations sometimes employ a confederate.

162
Q

confederate

A

introduced as another participant in a study. He says or does things experimenters need him to do.

  • when talking to a confederate, the participants think they are in an actual social situation and will behave normally.
  • -> this achieves experimental realism
163
Q

what are some downsides of staged manipulations?

A

they are harder to interpret and harder to replicate. The experiment is not very controlled and so the results are unclear.
straight forward manipulation is used more than staged for those reasons.

164
Q

manipulation strength

A

try to make manipulations as strong as possible; Making the levels of the independent variable maximally different while keeping everything else between the two group the same.
(increase the chances of seeing effects)

165
Q

Manipulation checks

A

used to try to measure whether the manipulation of the independent variable leads to the psychological responses they were aiming for.
- can be measured after experiment to avoid demand characteristics.

166
Q

what are the pros of manipulation checks?

A

pros:
- can be used in a pilot study to see if the manipulation will be effective
- can tell you if the results are due to the fact that the manipulation is incorrect.

167
Q

self-report measure

A

can be used to measure explicit attitudes, liking for someone, judgements, intended behaviours, values, emotional states, confidence, and other human behaviour stuff.
Techniques: paper and pencil questionnaire, face to face, interviews, online questionnaire.

168
Q

behavioural measures

A

A direct observation of behaviours.
ex: self-control, creativity (number of new ideas per min), reaction time, facial expression of emotion, attention, memory, conformity.
Measure techniques: counter, timer, lie detector, camera, writing sample.

169
Q

Physiological measure

A

GSR, EMG, EEG, blood analysis, saliva analysis, heart rate, breathing rate, blood pressure, FMRI, MRI.
used to measure: stress (by GSR, or measure cortisol in saliva), genetic markers for mental illness (blood analysis), damage to brain (MRI).
EMG measures muscle tension
ECG measure heartbeat
EEG electrical activity of brain
FMRI scans brain when participant is doing cognitive work.

170
Q

sensitivity

A

how sensitive (accurate) your operational definition is in detecting differences in dependent variable. (ex: timer is super sensitive)

171
Q

ceiling effect

A

the independent variable might appear to have no effect on dependent measure only because participants quickly reach the maximum performance level cuz task is too easy. Ex; memory task that is way too easy

172
Q

floor effect

A

task too hard so participants can’t produce accurate results.

173
Q

multiple measures

A

various operational definitions in one experiment to measure something.

174
Q

Setting the stage

A

plan the experience of the experiment from a participant’s point of view.

  • prepare informed consent form
  • prepare practice script
175
Q

Demand characterisitics

A

any feature of a study that might inform participants of its purpose and consequently affect their behaviour.

  • you can use deception to solve this
  • or you can put a bunch o filler items in a questionnaire
176
Q

Placebo group

A

participants receive a pill or injection containing an inert, harmless substance and does not contain drug given to experimental group.

177
Q

balanced placebo design

A

Ex:

group1: given nicotine- told nicotine
group2: given no nicotine- told no nicotine
group3: given nicotine- told no nicotine
group4: given no nicotine-told nicotine

178
Q

waitlist control condition:

A

participants in the control conditions may be given the treatment after the study is completed.

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