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Research Methods Flashcards

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1
Q

The Scientific Method (7)

A 
Construct a Theory
Generate a Hypothesis
Choose Research Method
Collect Data
Analyze Data
Report Findings
Revise Existing Theory
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2
Q

Theory

A

a general set of ideas about the way that the world works. Guides the creation of a hypothesis. (Begin by studying existing info and studies to help construct a theory)

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3
Q

Hypothesis

A

testable statements guided by theories that make specific predictions about the relationship between variables.

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4
Q

Research Method

A

appropriate way to test hypothesis and collect data

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5
Q

Collect Data

A

outcomes of research method

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6
Q

Analyze Data

A

discover trends/relationships revealed by research. Leads to the decision to accept or reject original hypothesis

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7
Q

Report Findings

A

making formal presentations at scientific meetings with the goal of publishing work. There is a rigorous review process to ensure accuracy.

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8
Q

Revise Theories

A

Individual scientists and scientific community review all findings on a topic to revise existing theories that define out current understanding of the world. Because science and research are dynamic processes, theories are continually being revised to account for new info.

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9
Q

Experiment

A

Scientific tool used to measure the effect of one variable on the other

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10
Q

Independent Variable

A

variable manipulated by the scientists

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11
Q

Dependent Variable

A

variable being observed by the scientist

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12
Q

Experimental Group

A

receives the manipulation of Independent Variable

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13
Q

Control Group

A

does not receive manipulation of Independent Variable. Serves as an accurate comparison in an experiment.

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14
Q

Differences between Experimental and Control Groups

A

participants in bot groups should be as similar as possible to minimize differences between them and therefore outside factors that may sway the results. In this way, the only difference between them should be the independent variable, and any outcome is the cause of the manipulation of it.

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15
Q

Within-Subjects Design

A

manipulating the Independent Variable within each participant to minimize the effect of external variables on the dependent measure

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16
Q

Practice Effect

A

Improved performance over the course of an experiment due to becoming more experienced

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17
Q

Between-Subjects Design

A

one group acts as the control group

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18
Q

Confounding Variable

A

a variable other than the Independent Variable that has an effect on the results

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19
Q

Selecting Subjects

A

results from very specific groups of participants cannot be generalized to other groups

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20
Q

Population

A

the full group of individuals you are seeking to understand

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21
Q

Sample

A

represents the population, and must accurately reflect the population to allow generalizing of results

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22
Q

Random Sample

A

choosing a sample at random from the entire population to avoid bias

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23
Q

Random Assignment

A

assigning subjects to either the experimental or control group at random to avoid any biases that may cause differences between the groups of subjects

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24
Q

Placebo Effect

A

effect that occurs when an individual exhibits a response to a treatment that has no related therapeutic effect (sugar pills)

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25
Q

Subject/Participant Bias

A

when a participant’s actions in an experiment influence the results outside the manipulations of the experimenter

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26
Q

Blinding

A

When participants do not know whether they belong to the control group or experimental group, or which treatment they are receiving. This removes the placebo effect.

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27
Q

Experimenter Bias

A

Actions made by the experimenter, intentionally or not, to promote the result they hope to achieve. Reduced if the experimenter does not know who belongs to which group.

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28
Q

Double-Blind Studies

A

experiments in which neither the experimenter nor the participants know which group each participant belongs to.

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29
Q

Descriptive Statistics

A

Allow us to summarize, interpret and present collected data.
Presents information about a data at a glance to get an overall idea of results (includes measures of central tendency and standard deviation)

30
Q

Histogram

A

A type of graph used to report the number of times groups of values appear in a data set
The Y-axis represents the number of values that fall into a given ‘bin’ along the x-axis.

31
Q

Frequency Distribution

A

type of graph illustrating the distribution of how frequently values appear in the data set. Shows how likely each outcome is to occur.

32
Q

Normal Distribution

A

a distribution with a characteristic smooth, symmetrical, bell-shaped curve containing a single peak.

33
Q

Mean

A

the average value of a data set, calculated by adding together all the points in a data sets and dividing by the number of items in the set.

34
Q

The Effect of Outliers

A

extreme points distant from the other in a data set that dramatically changes the mean

35
Q

Median

A

the centre value in a data set when the set is arranged numerically, calculated by eliminating the highest and lowest value repeatedly until only one value remains. If 2 values remain, find the mean of those values. Cannot be affected by outliers.

36
Q

Mode

A

the value in a data set that occurs most frequently and is used for non-numerical data sets.

37
Q

Disadvantages of Using Measures of Central Tendency

A

only focus on the centre value, and not how other values fall around that point.

38
Q

Measures of Variability

A

second group of static that reviews the spread and distribution of a data set.

39
Q

Standard Deviation

A

measure of average distance of each data point from the mean

40
Q

Inferential Statistics

A

statistics that allow us to use results from samples to make inferences about overall, underlying populations.
There will always be random variability due to chance, and not all participants are expected to behave equally.

41
Q

Hypothesis Testing

A

Hypothesis is proven if data is being collected from two different distributions (with some overlap)
Hypothesis is disproven if data is being drawn from single distribution because there is no difference between the two groups.

42
Q

T-Test

A

A statistical test that considers each data point from both groups to calculate the probability that two samples were drawn from the same population. Used to compare the difference between the data from the control and experimental group.

43
Q

P-Value

A

A value expressing the probability calculated by te T-Test

44
Q

Statistical Significance

A

if the results of the T-Test (P-Value) are less than 0.05/5% then they are statistically significant.
This means that the difference between the two groups is due to some true difference and not random variation.

45
Q

Observational Studies

A

studies where scientists observe the effect of variables they’re interested in without performing any specific manipulation. Can eliminate the issue of ethics that arise in experimental designs.

46
Q

Correlation

A

a measure of the strength of the relationship between two variables.

47
Q

Correlation Coefficient

A

a numerical index that describes the degree of relationship (strength and direction) between two variables

48
Q

Perfect Positive Correlation

A

Value of +1 –> As one variable increases, the other increases

49
Q

Perfect Negative Correlation

A

Value of -1 –> As one variable increases, the other decreases.

50
Q

Zero Correlation

A

As the correlation between two variables gets weaker, the correlation coefficient approaches zero. 0 = no correlation.

51
Q

Correlation Versus Causation

A

Correlation does not equal causation! Just because two values are correlated, it doesn’t mean that one variable as causing an effect on another.

52
Q

Anecdotal Evidence

A

information evidence gathered from others or from one’s own experiences

53
Q

Case Study

A

an in-depth investigation of an individual person or a small group of people, often over an extended period of time

54
Q

Constant

A

a feature or quality that always takes the same value across all situations.

55
Q

Construct Validity

A

the extent to which there is evidence that a test measures a particular hypothetical contruct

56
Q

Empiricism

A

The philosophical perspective that states that knowledge should be gained by direct observation of the world as it is, as opposed to rational perspectives that used logic and reason to determine how the world ought to be.

57
Q

Interview

A

a research tool during which the investigator asks the participant questions, often these may be structured or semi-structured in nature.

58
Q

Naturalistic Observation

A

a descriptive research method in which the researcher engages observation if behaviour in real-world studies

59
Q

Paradigm

A

a set of assumptions and ideas about what kind of research questions can be asked and how they can be answered.

60
Q

Operational Definition

A

this describes the actions or operations that will be made to objectively measure or control a variable

61
Q

Psychological Test

A

a standardized measure of a sample of a person’s behaviour

62
Q

Questionnaire

A

a research tool in which a participant responds to a written list of times or questions

63
Q

Raw Data

A

Data collected from a study or experiment that has yet to be assessed using statistical analyses

64
Q

Reliability

A

the measurement consistency of a test

65
Q

Replication

A

the repetition of a study to see whether the earlier results can be duplicated, often times by independent researchers

66
Q

Sampling Bias

A

a problem that occurs when a sample is not representative of the population from which it was drawn

67
Q

Scientific Method

A

the formal methods, primarily the set of techniques and concepts, used to examine and answer questions of a scientific nature

68
Q

Social Desirability Bias

A

a tendency to give socially approved answers to questions about one’s self

69
Q

Type 1 Error

A

saying the Independent Variable as an effect on the results when it really doesn’t

70
Q

Type 2 Error

A

saying the Independent Variable has no effect when it really does.

Psychology (12 decks)

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