Research Methods Flashcards

1
Q

Scientific Method

A

The process of basing one’s confidence in an idea on systematic, direct observations of the world, usually by setting up research studies to test ideas.

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2
Q

Theory-Data Cycle

A

The process of the scientific method in which scientists collect data that can either confirm or disconfirm a theory.

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3
Q

Theory

A

A set of propositions explaining how and why people act, think, or feel.

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4
Q

Hypothesis

A

A prediction about what will happen based on the theory.

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5
Q

Data

A

A set of empirical observations that scientists have gathered.

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6
Q

Replication

A

When a study is conducted more than once on a new sample of participants and obtains the same basic results.

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7
Q

Variable

A

Something of interest that varies from person to person or situation to situation.

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8
Q

Measured Variable

A

A variable whose values are simply recorded.

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9
Q

Manipulated Variable

A

A variable whose values the researcher controls, usually by assigning different participants to different levels of that variable.

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10
Q

Operational Definitions

A

Specific ways of measuring or manipulating an abstract variable in a particular study (usually turning a variable into a number).

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11
Q

3 Types of Research Methods

A

1) Descriptive
2) Correlational
3) Experimental

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12
Q

Descriptive Research

A

A type of study in which researchers measure one variable at a time (tells us what do people do on average).

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13
Q

Correlational Research

A

Tells us what kinds of people do this or what’s associated with what. Measuring the degree to which two variables are related or predict one another (co-related).

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14
Q

Experimental Research

A

A study in which one variable is manipulated and the other is measured. Can provide evidence that one variable causes another (tells us why do people do this or what causes these behaviours). A means of determining the cause of events.

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15
Q

Sample

A

The group who participated in research and who belong to the larger group (the population of interest) that the researcher is interested in understanding. A limited number or people from the population.

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16
Q

Population of Interest

A

The full set of cases the researcher is interested in ex. New Zealand adults, North Americans, people who buy coffee at Starbucks, Twitter messages, and etc.

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17
Q

Random Sampling

A

A way of choosing a sample of participants for a study in which participants are selected without bias ex. by dialing random digits on the telephone or pulling names out of a hat.

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18
Q

Naturalistic Observation

A

An observational research method in which psychologists observe the behaviour of animals and people in their normal, everyday worlds and environments.

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19
Q

Observational Research

A

A descriptive research method in which psychologists measure their variable of interest by observing and recording what people are doing.

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20
Q

Case Study

A

An observational research method in which researchers study one or two individuals in-depth, often those who have a unique condition.

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21
Q

Correlational Research

A

A type of study that measures two (or more) variables in the same sample of people and then observes the relationship between them.

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22
Q

Positive Correlation

A

High scores on one variable go with high scores on the other (and low scores go with low). The variables tend to occur together (positive trend).

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23
Q

Negative Correlation

A

A relationship between two variables in which one variable increases as the other decreases and vice versa. The variables tend to occur at opposite times (negative trend).

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24
Q

Third-Variable Problem

A

For a given observed relationship between two variables, an additional variable that is associated with both of them, making the additional variable an alternative explanation for the observed relationship. A third variable causes the two other variables (Z causes X and Y).

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25
Q

Random Assignment

A

A procedure used in experimental research in which a random method is used to decide which participants will receive each level of the independent variable.

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26
Q

Experimental Group

A

In an experiment, a group or condition in which some proposed cause is present.

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27
Q

Temporal Precedence

A

One variable must clearly come before the other.

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28
Q

Validity

A

The appropriateness or accuracy of a conclusion or decision (how accurate is it?).

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29
Q

Construct Validity

A

The specific assessment of how accurately the operationalizations used in a study capture the variables of interest. The extent to which a test/assessment actually measures what it says it does.

30
Q

Reliability

A

The degree to which a measure yields consistent results each time it is administered. A measure’s ability to produce consistent results (can we count on it to behave consistently?) (how precise is it?).

31
Q

External Validity

A

The degree to which it is reasonable to generalize from a study’s sample to its population of interest.

32
Q

Internal Validity

A

The ability of a study to rule out alternative explanations for a relationship between two variables. One of the criteria for supporting a causal claim.

33
Q

Confound

A

An alternative explanation for a relationship between two variables. When two experimental groups accidentally differ on more than just the independent variable which causes a problem for internal validity.

34
Q

Descriptive Statistics

A

Graphs or computations that describe the characteristics of a batch of scores, such as its distribution, central tendency, or variability.

35
Q

Frequency Distribution

A

A descriptive statistic that takes the form of a bar graph in which the possible scores on a variable are listed on the x-axis and the total number of people who had each score is plotted on the y-axis.

36
Q

Mean

A

The average.

37
Q

Median

A

The middle when ordered from lowest to highest.

38
Q

Mode

A

Most common/frequent.

39
Q

Variability

A

The extent to which the scores in a batch differ from each other.

40
Q

Standard Deviation

A

A variability statistic that calculates how much, on average, a batch of scores varies around its mean.

41
Q

Effect Size

A

Describes the magnitude of the relationship between manipulated or measured variables.

42
Q

Inferential Statistics

A

Use sample results to infer what is true about the broader population.

43
Q

Statistical Significance

A

A process of inference that applies rules of logic and probability to estimate whether the results obtained in a study’s sample are the same in a larger population. What is the probability that the difference we found in our sample truly exists in the population?

44
Q

Null Hypothesis

A

The hypothesis that the hypothesis is false (the claim that the effect being studied does not exist). It is the opposite of the hypothesis.

45
Q

P-Value

A

Measures the probability of obtaining the observed results assuming that the null hypothesis is true (between 0 and 1).

46
Q

Low P-Value

A

<0.05. A significant result. Does not mean that the hypothesis is true, it just means that the data are unlikely to occur under the null hypothesis.

47
Q

High P-Value

A

> 0.05. A nonsignificant result. Does not mean that the hypothesis is false, it means that the data are fairly likely to occur under the null hypothesis.

48
Q

False Positive

A

A statistically significant finding that does not reflect a real effect.

49
Q

P-Hacking

A

Changing the data to manipulate the p-value.

50
Q

Open Science

A

The practice of sharing one’s data, hypotheses, and materials freely so others can collaborate, use, and verify the results.

51
Q

Preregistration

A

A researcher’s public statement of a study’s expected outcome before collecting any data.

52
Q

Institutional Review Board (IRB)

A

A local panel of researchers, teachers, citizens, and others who determine whether a research study lives up to the community’s ethical standards.

53
Q

Canadian Council on Animal Care (CCAC) 3Rs

A

1) Replacement (try to find alternatives to using animals).
2) Refinement (modify procedures to minimize or eliminate animal distress).
3) Reduction (try to use the least amount of animals).

54
Q

Hindsight Bias

A

The tendency to believe, after learning an outcome, that one would have foreseen it (“I-knew-it-all-along” phenomenon. Makes us overconfident in our power of deduction/intuition).

55
Q

The Scientific Method

A

1) Observations
2) Development of Theories
3) Generate Hypotheses
4) Design a Research Study
5) Collect Evidence

56
Q

Theory

A

A set of principles that explain, organize, and predict events (what is known about this behaviour already?).

57
Q

Theory of Catharsis

A

Negative feelings build up and create pressure if not vented. If this tension continues to build, people will explode. Releasing emotions decreases the pressure or tension.

58
Q

Hypothesis

A

A testable prediction that is based on (derived from) your theory (what evidence would confirm my theory? Disprove it?).

59
Q

Operational Definitions

A

A clear statement of the procedures (operations) used to define research variables in a study (describes how we will measure our variables).

60
Q

Descriptive Approaches

A

1) Surveys/Questionnaires (self-report)
2) Naturalistic Observation (observe and record behaviour as it naturally occurs. No attempt to control the situation).
3) Case Studies (observation technique in which one person is studied in depth in hope of revealing universal principles).

61
Q

Correlation Coefficient (r)

A

A statistical measure of the relationship between two variables. 0 is no relationship. +/-1 is a strong relationship.

62
Q

r = 0

A

No relationship.

63
Q

r = +/-1

A

Strong relationship.

64
Q

Directionality Problem

A

When two variables are measured at the same time it is impossible to know which variable causes the other variable (Does X cause Y? OR Does Y cause X?).

65
Q

Why Not Always Use an Experiment?

A

1) Unethical (ex. heavy binge drinking, unsafe sexual practices)
2) Challenging to Carry Out (time taxing)
3) Expensive (ex. equipment needed, participant compensation)
4) Hard to Collect Large Samples
5) Not Interested in Causation (depends on research goals)
6) Cannot Always Randomly Assign Variables (ex. gender, race)

66
Q

What Makes Good Research?

A

1) Objective Measurement (measures are reliable and valid)
2) Generalizable (can broader conclusions be made towards the population?)
3) Unbiased
4) Made Public
5) Replicated

67
Q

Test-Retest Reliability

A

It doesn’t matter when the test is conducted, the results should be the same or similar.

68
Q

Interrater Reliability

A

The people doing the observations or grading should have the same or similar result.

69
Q

Population

A

Everyone/everything we are interested in.

70
Q

Alternative Hypothesis

A

Matches/supports the hypothesis.