IB Psychology- Quantitative Research

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Random Sampling

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Quantitative research basic terms

20 Terms

1

Random Sampling

Every member of the target population has an equal chance of becoming a part of the sample.

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2

Stratified Sampling

Essential characteristics for the study are decided, then the distribution of these characteristics in the general population is studied.

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3

Convenience Sampling

Easily available participants are recruited.

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4

Self- Selected Sampling

It takes place by recruiting volunteers. It is quick, easy, and has wide coverage.

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5

Independent Measures Design

Involves random allocation of participants into groups and a comparison between these groups. The IV is manipulated and there can be more than one IV.

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6

Matched Pairs Design

Matching is used to form the groups. It is used to make sure that groups are equivalent.

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7

Repeated Measures Design

The goal is to compare conditions rather than groups of participants.

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8

Construct Validity

Characterizes the quality of operationalizations.

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9

Internal Validity

Characterizes the quality of the experiment.

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10

Population Validity (external)

Generalizability from the sample to the target population, high when sample is representative.

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11

Ecological Validity (external)

Generalizability of the experiment to other settings or situations.

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12

Selection Bias

Mistakes in sampling and creating groups.

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13

History Bias

The outside events that happen to a participant/ group (ex. noise coming from outside in a memory test, one group is closer to the noise)

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14

Maturation Bias

Participants going through natural development (ex. child participants may grow in between two experiments)

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15

Testing Effect Bias

Doing a test for the second time affecting the results, thus the researcher not knowing if the results changed because of the training given or familiarity.

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16

Instrumentation Bias

The instrument measuring the DV changing slightly (ex. the observer being more tired during one of the experiments)

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17

Regression to the Mean Bias

The DV being extremely high or low (when a person retakes a test, their score tends to get closer to the average score)

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18

Experimental Mortality Bias

Some participants dropping out during an experiment, may become a problem if dropouts aren’t random (ex. if the dropouts are higher in the experimental group, the experiment cannot go on)

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19

Demand Characteristics Bias

Participants understanding the aim of the study and altering their behavior accordingly (in order to eliminate this, the experiment should be a blind experiment)

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20

Experimenter Bias

The researcher unintentionally affecting the results of a study (in order to eliminate this bias, the experiment should be a double blind experiment)

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