Chapter 4 Flashcards

1
Q

What are the 2 major types of studies?

A

Experiments and non-experimental designs

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2
Q

What can a research idea be broken into?

A

a set of variables

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3
Q

What is a variable?

A

any event, situation, behaviour or individual characteristic that varies - that is, can differ in some way (e.g. quantity, size degree)

things that vary (between people), things that can have more than one value.

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4
Q

What properties will variables have?

A

true numeric, or quantitative, properties or meanings

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5
Q

What will psychological variables have?

A

at least 2 specific levels or values

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6
Q

What is an example of a categorical variable?

A

nationality. They are different but they do not differ in amount or quantity.

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7
Q

How are relationships studied in the non-experimental method? What might this include?

A

by measuring or observing the variables of interest

This could include asking people the describe their behaviour, directly observing their behaviour, recording physiological responses, or examining publicly available information. Once data on both variables are collected, the researchers use statistics to determine whether there is a relationship between them.

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8
Q

What is the non-experimental method?

A

measuring variables to determine whether they are related to one another; also called the correlation method.

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9
Q

How does the measure of variables under the experimental method contrast to the non-experimental method?

A

non-experimental methods that measure al the variables of interest the experimental method involves direct manipulation of one variable, control of several other variables (those not of interest), and then measurement of an outcome variable (hypothetically affected by the manipulated variable)

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10
Q

What implications do the differences between experimental and non-experimental methods have?

A

impact the types of conclusions we can draw from the results

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11
Q

What is the experimental method?

A

a method that tries to determine if variables are causally related, by manipulating one variable (the independent variable), controlling all other variables, and then measuring the effect on some outcome (the dependent variable)

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12
Q

what is operationalization?

A

definition of a variable that specifies the operation used to measure or manipulate it within a specific study; also known as an operational definition

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13
Q

What are the three general categories for variables?(broad, not associated with values)

A
  • a situational variable
  • a response variable
  • a participant variable
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14
Q

What is a situational variable?

A

a characteristic of some event or environment external to a participant, to which they are exposed

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15
Q

What is an example of a situational variable?

A

length of a passage being read, the number of people around you when writing a test, the credibility of a person trying to persuade you, or different instructions on what to focus on when recalling an event.

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16
Q

How do situational variables apply to each design type?

A

situational variables can be measured in any design or manipulated in experimental designs.

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17
Q

What is a response variable?

A

A participant’s reaction to some event

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18
Q

What are examples of response variables?

A

reaction time in response to a stimulus, performance on a cognitive task, and emotional reactions

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19
Q

How do response variables apply to each design type?

A

response variables can be measured in either experimental or non-experimental designs

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20
Q

What is a participant variable?

A

a pre-existing characteristic or aspect of a person that is of interest

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21
Q

What are examples of participant variables?

A

cultural background, age, intelligence, and personality traits (ex: extraversion).

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22
Q

How do participant variables apply to each design type?

A

sometimes participant variables are related to other variables in non-experiments, and sometimes they are used to group participants for comparison on some response variable.

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23
Q

Why must variables be operationalized?

A

so that they can be studied empirically

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24
Q

What is a prediction in the context of operationalization?

A

a prediction is a statement of the hypothesis that has been translated into the specific operationalization pf the particular study

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25
Q

What do researchers have to do with operationalized variables? Why?

A

they must describe precisely how they operationalize all variables and argue why there operationalization is appropriate

These details help other researchers evaluate the study, and also potentially attempt to replicate the study.

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26
Q

What is ensuring that operationalizations are precise crucial for?

A

making claims about these variables

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27
Q

What happens if our operationalization captures more than just the variable of interest?

A

it makes it difficult or impossible to interpret the results of research

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28
Q

What are confounding variables?

A

Variables that are not of interest, but are uncontrolled or impossible to separate from the variable of interest , and that can also explain the pattern of results. These confounds make interpreting the results difficult or impossible, as we do not know what is responsible for an effect or association.

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29
Q

When can confounds occur?

A

confounds can occur for variables that are merely measured, but also in experiments when an independent variable is not manipulated in a precise way

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30
Q

What do researchers need to do to address confounds? Why?

A

when measuring variables, researchers must try to anticipate potential confounds and measure them as well, in order to rule them out statistically

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31
Q

How do researchers decide a method for operationalizing a variable?

A

based on the particular problem under study, the goals of the researxh, and other considerations such as ethics and cost

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32
Q

What does our best understanding of a variable involve?

A

studying it using a variety of operationalizations

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33
Q

What does a typical non-experimental design allow u to predict?

A

covariation between variables also known as the correlational method

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34
Q

What are correlational methods?

A

methods in which variables are observed but not manipulated

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35
Q

What should we not confuse correlational methods with?

A

correlational statistic which can be calculated for both experimental and non-experimental designs.

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36
Q

What do correlational designs allow us to consider?

A

many different kinds of relationships between variables

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37
Q

What are the 4 most common relationships found in research?

A
  1. the positive linear relationship
  2. the negative linear relationship
  3. the curvilinear relationship
  4. when there is no relationship between variables
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38
Q

What is the mediated relationship? What is this often used to describe?

A

describes how the relationship between 2 variables can be explained via a third variable

  • often used to describe psychological processes
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39
Q

What is a positive linear relationship? What is a common example?

A

a relationship between 2 variables in which increases in the values of the first variable are accompanied by increases in the values of the second variables

  • age and weight have a positive linear relationship
40
Q

What is a negative linear relationship?

A

a relationship between 2 variables in which increases in the values of the first variable are accompanied by decreases in the value of the second variable

41
Q

What is a curvilinear relationship? What’s a typical example?

A

a relationship between 2 variables in which increases in the values of the first variable are accompanied by both increases and decreases in the values of the second variable, resulting in a curved line depicting this relationship rather than a straight line

the relationship between happiness and halloween candy. at the beginning you are really happy but then it peaks and decreases at certain levels.

42
Q

What is the inverted U relationship?

A

when the point is at the bottom rather than at the top

43
Q

What does the no relationship graph look like?

A

a simple, flat, horizontal line.

44
Q

What is the correlation coefficient?

A

a number that allows us to determine the strength of a relationship

45
Q

What is a mediating variable?

A

a psychological variable that occurs between an event and a behavioural response (helps to explain the relationship between 2 other variables)

46
Q

What do models of mediated relationships provide for us? What can we do with this knowledge?

A

insight into how and why variables are related to one another

With this knowledge we can begin to explore possible interventions to help improve the relationship between 2 variables by suggesting tools to improve another aspect that eventually improves the relationship between the variables of interest.

47
Q

What is a construct?

A

another name for an abstract variable, idea, or phenomenon

48
Q

Are relationships between variables perfect?

A

almost never

49
Q

What would a perfect relationship between variables mean?

A

if we knew the value of one variable we would know exactly what the value would be for the other variable.

50
Q

What do correlations capture? What is likely as a result? What does this tell us about group data and the individual? What is an analogy for this? What does this mean for validation of a trend?

A

the overall trend of relationships, averaging across many people’s data. They do not mean that everyone absolutely everyone experienced the same relationship between variables.

as a result, individual deviations from the general pattern are likely.

This is why you cannot use the results based on group data to make accurate guesses about any one individual (similar to how we should not use stereotypes about groups to apply to individuals)

This also means that and individual who does not fit into the overall trend doesn’t invalidate the group trend

51
Q

What does uncertainty mean?

A

means that there is something unknown or that we’re not confident about knowing something

52
Q

What is the word that scientists use to explain aspects of a phenomenon that we can’t predict or explain or that result from variables not of interest to us?

A

random variability or error variability

53
Q

How does research aim to reduce random variability?

A

by identifying systematic relationships between variables

54
Q

When are relationships between variables stronger?

A

When there is less error variability

55
Q

What is a way in which researchers seek to reduce random variability? Why?

A

conducting additional research

you may be able to identify other variables that are also related.

56
Q

Is direction of correlation or third variables mutually exclusive?

A

no. One thing being true doesn’t mean the others aren’t also true. All three possibilities can be true at the same time/

57
Q

What is temporal precedence?

A

what comes first in time when trying to figure out correlation/causality

58
Q

What is the difference between a third variable and a confounding variable?

A

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

59
Q

What is the independent variable? What is this also thought of as?

A

the variable in an experiment that is manipulated by the researcher, in order to observe its effect on some outcome variable (i.e the dependent variable)

thought of as the “cause”

60
Q

What is the dependent variable?

A

the variable measured in an experiment that represents some outcome of interest, which is hypothesized to be affected by the causal variable (ie the independent variable)

61
Q

What axis is the independent variable always placed on?

A

horizontal (x) axis

62
Q

What axis is the dependent variable always placed on?

A

the vertical (y) axis

63
Q

Why is a bar graph used in experimental methods?

A

because the experimental conditions are separate categories

64
Q

Does research always have to have one independent and one dependent variable? When might this not be the case?

A

no.

some research focuses primarily on the independent variable and the researcher studies the effect of a single independent variable on numerous behaviours

other research focuses primarily on the dependent variable and the researcher focuses on how various independent variables affect that one behaviour.

65
Q

What is one reason that experiments allow for causal inferences?

A

temporal precedence

66
Q

How do experiments have temporal precedence compared to non-experiments?

A

in many non-experimental designs, both variables are measured at the same time so we don’t have information about what comes first. In an experiment, we manipulate the independent variable, and then we measure its effects on the dependent variable, so we have this temporal information.

67
Q

How do experiments attempt to eliminate the influence of all other variables except the one being manipulated?

A

by trying to ensure that every other feature of the control and experimental conditions is held constant, except for the independent variable.

68
Q

How do we control for something that cannot be held as consistent across conditions? Example?

A

we ensure that its affects are random and therefore hopefully evenly distributed across conditions.

by randomly assigning people to our experimental or control conditions, the influence of extraneous variables associated with these participants that we’re not interested in should be approximately equal across the conditions.

69
Q

For an experiment, when is covariation demonstrated?

A

when participants in an experimental condition exhibit a different effect relative to participants in a control condition.

70
Q

What do alternative explanations usually involve?

A

the possibility that some confounding variable could be responsible for the observed relationship

71
Q

How do researchers in experiments try to rule out alternative explanations?

A

by using random assignment and different forms of experimental control (e.g. control conditions)

72
Q

When is an experiment said to have high internal validity?

A

when a researcher designs an experiment hat meets all three criteria for cause and effect

73
Q

What does the term validity refer to in research?

A

refers to concepts of both truth and accuracy, and there are many types of validity.

74
Q

What does internal validity refer to?

A

a quality experiments, referring to the certainty with which it can support causal inferences; the degree to which the outcomes observed can be attributed to the manipulated independent variable rather than some alternative explanation.

75
Q

What is experimental control?

A

This quality of good experimental design is achieved when only the independent variable of interest varies across conditions, with all other features kept the same across conditions.

76
Q

What is random assignment?

A

in an experiment, using chance to determine which participants end up in which conditions, in order to control for the effects of extraneous variables not of interest to the researcher.

77
Q

If conditions were confounded with time of day, what would we have difficulty inferring?

A

whether differences observed between conditions for the dependent variable are a result of the manipulated independent variable or simply the time of day

78
Q

What does some philosophers, scientists, and students argue about cause and effect relationships?

A

that cause and effect relationships are established only if cause is both necessary and sufficient for the effect to occur

79
Q

What do we mean by the cause must be necessary?

A

the cause must be present for the effect to occur.

80
Q

What do we mean by the cause must be sufficient?

A

to be sufficient the cause will always produce the effect

81
Q

Why is the necessary and sufficient requirement for establishing cause rare in psychology?

A

because most psychological outcomes have many different causes, it is extremely rare that just one cause is sufficient to explain some phenomenon

82
Q

What does research on numerous variables eventually lead to?

A

an understanding of a whole causal network in which the number of variables are involved in complex patterns of cause and effect.

83
Q

What are some of the draw backs of experimental designs?

A
  • because lab experiments are so highly controlled, there’s a question about the degree to which we can learn about the real world from these results
  • not all research questions are amenable to the experimental design
84
Q

What is one way that concerns about generalizability can be addressed?

A

by attempting to conduct an experiment in a field setting

85
Q

What is a field experiment?

A

An experiment that is conducted in a natural setting, out in the real world, rather than in a laboratory

86
Q

Where do many field experiments take place?

A

public spaces, like street corners, malls or online

87
Q

What is the advantage of field studies? What is the disadvantage?

A

the advantage of field studies is that the investigation takes place in a natural context. The disadvantage is that the researcher loses the ability to control every aspect of the situation.

88
Q

When is it more likely for the opposite effects to be observed in a field setting as compared to the lab?

A

When only small effects were observed in the laboratory setting.

89
Q

Why might we have to use non-experimental methods?

A

if manipulating a variable would be unethical or impractical

90
Q

How are participants usually assigned in non-experimental methods? Example?

A

usually they are assigned into conditions based on some real world aspect that they have. For example; if studying the affect of having a working mother on children, one group of children will have working mothers and the other group will not.

not assigned through random assignment

91
Q

When random assignment conditions are not possible and these designs compare groups but cannot support causal claims, what are they called?

A

quasi experimental designs

92
Q

When are causal claims irrelevant/ when are experiments unncessary?

A

when the research goal is to describe events accurately

93
Q

Is it possible to design measures that increase the accuracy of predicting future behaviour without being concerned with ultimate causes?

A

yes

94
Q

is it possible that issues of cause and effect may not be of concern when trying to predict people’s future behaviour?

A

yes

95
Q

What must researchers do when developing tests and questionnaires designed to predict future behaviour?

A

they must conduct research to demonstrate that the measure does, in fact, relate to the behaviour in question

96
Q

What does a complete understanding of any phenomenon require? Why?

A

research using multiple methods (experimental and non experimental)

the strengths of one method might compensate for the weaknesses of another. Even though experimental research may provide causal information, a non-experimental study coupled with an experimental study can help enhance support for a hypothesis (ex: music lessons increase in inteligence (experimental), music lesson overtime continue ot increase intelligence? (non experimental))