Experiments, Ethics, Sampling, Aims & Hypotheses

Validity

Are accurate results achieved, does the test measure what you intend it to measure.

Reliability

Are consistent results achieved and would you get those same results if another person were to repeat the study

External validity

Whether the findings will generalise to other populations, locations, contexts and times and still hold true.

External Validity: Ecological validity AKA Mundane realism

Refers to the extent to which the findings of a research study are able to be generalised to real

External Validity: Population Validity

How representative the sample used is to other populations.

External Validity: Historical/Temporal Validity

Will the findings still be valid as society changes over the years e.g. will a study conducted about female behaviour in 1965, generalise to females today?

Internal validity

Within your measure, the IV is the only variable effecting the DV.

Internal Validity: Face Validity

The degree to which a procedure, especially a psychological test or assessment, appears effective in terms of its stated aims.

Internal Validity: Concurrent Validity

Whether a measure produces similar results for a participant as another test that claims to measure the same thing e.g. a participant completes a brand

A self

report

An observation

where you watch how people behave. Then psychologists make conclusions based only on what you can observe

Ethical concerns

CAN DO CANT DO WITH PARTICIPANTS IN PSYCHOLOGY

Androcentric

a sample that contains a large proportion of males.

Gynocentric

a sample that contains a large proportion of females.

Cultural bias

a sample that is too focused on one culture, isn’t representative of all cultures.

Ethnocentric

This is when research is generalised (trying to apply) to other cultures without considering how cultures are different.

Population validity

Being able to generalise results from our sample to the target population and still hold true.

Opportunity sampling

Anyone who is available at the time of your research. Strengths: Can help to collect participants with similar characteristics as people who share characteristics tend to segregate in the same areas so will help to generalise (apply) findings to a target population. Weaknesses: not always representative, researcher bias as they may only approach people who they feel will give them the results they want

Volunteer sampling

Participants choose themselves to take part in the study. They could be recruited through; using online email surveys, signing up or applying to take part, or responding to adverts or posters.

Random sampling

Every member of the population has a fair and equal chance of taking part. Strength: If you have a wide variety of differences in your sample, it is more likely to be generalisable to the wider population. Weakness: time consuming, impractical and sample could still be biased.

Stratified sampling

The population is divided into subgroups (strata) based on key characteristics (for example, age or gender), and participants are randomly selected from each subgroup in proportion to their presence in the population.

Systematic sampling

A systematic method is chosen for selecting from a target group, e.g. every fourth person in a list could be used in the sample. It differs from random sampling in that it does not give an equal chance of selection to each individual in the target group. Strength: reduces chance of researcher bias, increasing validity. Weakness: list could be arranged so every fourth person is male so that would make the sample unrepresentative

Independent measures design

Different participants participate in each condition, this means no practice effects

Single blind test – Participants are unaware of the condition that they are in meaning they are less likely to guess the aim of the study as they have not been given reasons or explanations as to the condition they are in reducing demand characteristics.

Double blind test – Neither the researcher or the participants are aware of which condition an individual is in reducing demand characteristics from the participants but also researcher bias is also reduced

Extraneous variables

Variables that could potentially effect the DV when we don’t want them to. Researchers only want the IV that we have created to effect the DV

Repeated measures design

When the same participants participate in each condition, counterbalancing can be used to reduce order effects

Matched pairs design

When different participants participate in each condition and each participant in one group is matched on a certain characteristic to another participant in the other group. For example: an experiment investigating the effect of sleep on Maths ability. Participants maybe matched on their Maths GCSE grade to ensure that it doesn’t act as a participant extraneous variable.

Experiment

A research method where the researcher manipulates an independent variable (IV) to observe the effect on a dependent variable (DV), while controlling extraneous variables to establish cause and effect.

Lab experiment

A study that is carried out in artificial settings with a highly controlled environment.

Field experiment

The researcher manipulates the IV themselvesA study that is carried out in a normal setting and is in a less controlled environment. The researcher manipulates the IV themselves

Quasi experiment

The researcher doesn’t and cannot manipulate the IV themselves. The IV is something which occurs in a participant for example age or gender

Natural experiment

The researcher does not and cannot manipulate the IV themselves. The IV is something which occurs externally, or in the environment

Research aim

what you aim to find out. For example: A study investigating the effects of chewing gum on memory recall

Research question

pretty much the aim, but phrased as a question. For example: Does chewing gum effect memory recall?

Null hypothesis

A statement predicting that there will be no difference or relationship between variables, and any observed effect will be due to chance.

Non directional hypothesis

Must use the word EFFECT since we're predicting that there will be an effect, but we are not predicting the direction of the effect, as it could go either direction.

Directional hypothesis

Use words, such as; POSITIVE, NEGATIVE, FEWER, HIGHER because we are predicting which way the effect is going.