AP Psych Vocab

Repeated Measures

Repeated measure design involves using the same subjects in each condition of an experiment, giving a group of subjects a driving test with no alcohol, followed at a later time by the same test after a pint of lager.

Pro: Variables are kept constant between conditions, better statistical tests due to less variation between conditions, and fewer subjects are required (used more than once).

Con: Order effects may become constant errors, demand characteristics may become an issue as subject acts differently, and different tests may be needed.

Independent Measures

Independent measures design involves using different subjects in each condition of the experiment, giving one group of subjects a driving test with no alcohol and a different group the same test after a pint of lager.

Pro: Order effects do not influence second condition, demand characteristics less of a problem, same test can be used.

Con: Subject variables may differ, confounding variable. Variation between conditions so worst statistical tests, and more subjects required so less economical.

Matched Pairs

Matched pairs design involves using different but similar subjects in each condition of an experiment. An effort is made to match the subjects in each condition in any important characteristics that might affect performance.

Pro: Subject variables more constant between conditions. Better statistic tests due to less variation between conditions, order effects and demand characteristics do not occur as subject in one condition experience, and same test can be used.

Con: Subject variables can never be perfectly matched, matching subjects is time consuming, more subjects are required since used only once.

Random Sampling

Occurs only when every number of a target population has an equal chance of being selected.

Pro: Provides best chance of unbiased representative sample of target population.

Con: Larger the target population, more difficult to sample randomly.

Stratified Sampling

Involves dividing the target population into important subcategories (or strata) and then selecting members of these subcategories in the proportion that they occur in the target population.

Pro: Deliberate effort is made to identify characteristics of a sample for it be representative of target population.

Con: Can be very time consuming.

Opportunity Sampling

Involves selecting those subjects that are around and available at the time. An effort may be made to not be biased in selecting particular types of subjects.

Pro: Quick, convenient, most common sampling

Con: May give unrepresentative sample and is often biased on part of researcher who may choose subjects that will be ‘helpful’

Self-selecting Sampling

Consist of those individuals who have consciously or unconsciously determined their own involvement in a study.

Pro: relatively convenient. Choice not biased by researcher, ethical if volunteers on informed consent

Con: often unrepresentative, bias on part of subject. Volunteers are unlike no volunteers.

Controlling extraneous variables and bias

Individual differences in subjects - control by large sample and random sampling of subjects to each condition to balance subject variables.

Artificiality in method (lab environments and operationalized variables lack ecological validity) - use a non-laboratory environment instead or increase definitions for operationalized variable

Order effects in subjects - use independent measures design instead or counterbalance the condition by getting half the subjects to perform condition A before condition B.

Demand characteristics (behaving differently) - use deception to hide research aim, use single blind method (subject doesn’t know which condition they are in)

Experimenter expectancy - use double blind method to avoid experimenter bias or use inter-observer reliability to overcome biased observation as observer no bias rates compared with researcher.

Procedure of distraction and confusion as both variables could be confound - standardized instructions should be clear and simple, so each participant has equal info

Reliability

Reliability of a method of measurement refers to how consistently it measures.

Internal reliability - how consistently a method measure within itself. If not standardized, would give distorted final scores. It could be checked for test items by split half method - correlating the results of half the items with the other half

External reliability - how consistently a method measures over time when repeated. Methods of measurement should give similar scores when repeated on same people. It could be checked for test items by test-, re-test method - correlating the results of the test conducted on one occasion with the results of the test conducted on a later occasion.

Validity

Validity - refers to whether it measures what it is supposed to measure - how realistically or truly variables have been operationalized.

Internal validity - refers to whether the results of a study were really due to the variables the researchers suggest were tested by their methodology.

External validity - refers to whether the results can be generalized if conducted in different environments or using different participants.

Validity Types

Face/Content Validity - Involves examining the content of the test to see if it looks like it measures what it is supposed to measure.

Concurrent validity - Involves comparing a new method or test with an already well established one that claims to measure the same variable(s).

Construct validity - Whether the test or method can be used to support the underlying theoretical constructs concerning the variable that it is supposed to be measuring

Predictive validity - refers to whether the test will predict future performance indicated by its results.

Ecological validity - whether a test or method measures behavior that is representative of naturally occurring behavior.

ethical guidelines for conducting research for animals

1. Avoid or minimize stress and suffering for all living animals

2. Always consider the possibility of other options to animal research

3. Be as economical as possible in the numbers of animals tested

Home Office License to conduct animal research is required before testing any animal.

Home Office monitors the conditions under which animals are kept, the researchers conducting the research, and the research projects allowed.

ethical issues in human reserach

Humans have right of protection and privacy.

Consent - informed consent all aspects of research should be revealed affecting consent. Authority or payment must not be used to pressure consent.

Deception - BPS ethical principles. Deception not allowed unless cost-benefit analysis of gains vs the discomfort of participant must be considered.

Debriefing - involves clarifying the principles’ understanding of the research afterwards and discussing or rectifying any consequences of the study to ensure that they leave the study in a similar a state as possible to when they entered it.

Withdrawal from the investigation - Any participant in a psychological study should be informed of their right to withdraw from testing whenever they wish.

Confidentiality - Under the Data Protection Act, participants and the data they provide should be kept anonymous unless they have given their full consent to make their data public. If participants are dissatisfied after debriefing they can demand their data is destroyed,

Protection of participants - Should leave studies in roughly same condition in which they arrived without suffering physical or psychological harm,

Observational Research - hidden observational studies produce most ecologically valid data but raise ethical issue of invasion of privacy.

Arguments for testing on animals

Research important enough for animal testing.

Makes sense to study simpler organisms first then generalize to humans.

Animals are more convenient, controllable, and have faster breeding cycles.

Humans have moral obligation to hep humans first and animal testing most close besides testing humans that is unethical.

There are many safeguards in place to prevent unnecessary use of animal research

Contributions of animal research include theoretical knowledge (many topics in psychology like aggression, abnormality), practical applications of animal findings (behavioral treatments), and practical uses of animals (animal helpers like guide dogs).

Reasons to not conduct animal reserach

Animals tested suffer greatly, is often unnecessary, humans are also mentally and physically qualitatively different to other animals where small differences may lead to exaggeration of similarity. Lab studies on animals are likely to lack ecological validity so less useful to generalize for humans.

Examples of animals suffering is Electric shocks, surgery, deprivation studies, and naturalistic observations (cause stress to animals and natural behavior disrupted).