IB Psychology- Quantitative Research

Quantitative research basic terms

Random Sampling

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

Stratified Sampling

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

Convenience Sampling

Easily available participants are recruited.

Self- Selected Sampling

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

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.

Matched Pairs Design

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

Repeated Measures Design

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

Construct Validity

Characterizes the quality of operationalizations.

Internal Validity

Characterizes the quality of the experiment.

Population Validity (external)

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

Ecological Validity (external)

Generalizability of the experiment to other settings or situations.

Selection Bias

Mistakes in sampling and creating groups.

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)

Maturation Bias

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

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.

Instrumentation Bias

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

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)

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)

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)

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)