Experiments Flashcards by Ashkan Rastani

Lab exp?

A laboratory experiment is an experiment conducted under highly controlled conditions, where accurate measurements are possible.

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Field exp?

A study that is conducted outside the laboratory in a “real-world” setting.

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Quasi exp?

An experiment with a naturally occurring IV.

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Control condition?

A condition that does not involve exposure to the treatment or intervention under study.

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Independent variable?

A variable that is manipulated by a researcher to investigate whether it consequently brings a change in another variable.

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Dependent variable?

The variable, which is measured and predicted to be dependent upon the IV

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Extraneous variable?

Any variable that you’re not investigating that can potentially affect the outcomes of your research study.

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Independent measures design?

An experimental design where different participants are used in each condition of the independent variable.

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Repeated measures design?

An experimental design where the same participants take part in each condition of the experiment.

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Matched groups design?

An experimental design where pairs of participants are matched in terms of key variables, such as age and IQ.

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Controls?

A condition that does not involve exposure to the treatment or intervention under study.

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Order effects?

The order of the conditions having an effect on the participants’ behaviour or/and outcome.

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Counter balancing?

A technique used to deal with order effects when using a repeated measures design.

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Advantages and disadvantages of repeated measures design?

ADV:
- Half the number of participants is needed to get the same amount of results as other designs

Eliminates participant variables

DVNTG:
- Order effects

Participants may eventually work out the aim/ purpose of the study and demand characteristics may arise.

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Advantages and disadvantages of independent measures design?

ADV:
- No order effects

Decreases the likelihood of demand characteristics

DVNTG:
- Results can be affected by participants variables.

Twice as many participants needed to get the same sample of results as in other designs

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Advantages and disadvantages of matched participant design?

ADV:
- Avoid order effects (participants only take part in one condition)

Participants’ variables are reduced ( partic. are matched in conditions).

DVNTG:

More complicated/time-consuming (pre-tests need to be carried out, to find matching characteristics)
Not everything can be matched
Twice as many participants are needed as in a repeated measures design, just to get the same amount of results

Advantages and disadvantages of Lab experiments?

ADV:
- Highly controlled

DVNTG:
- Low ecological validity

Advantages and disadvantages of Field experiments?

ADV:
- Increased ecological validity

DVNTG:
- Lack of control

Ethical issues as sometimes participants may not know they are being assessed

Advantages and disadvantages of Quasi-experiments?

AD:
- Usually high levels of eco validity, due to the involvement of a naturally occurring IV.

Can study the effects of variables that cannot be manipulated (weather).

DVNTG:
- cannot control extraneous variables

How can Participant variables be controlled?

matched participant design or repeated measures.
allocate participants to conditions randomly so that participant variables are more likely to be distributed evenly between conditions.

How can Situational variables be controlled (order effects) (environmental factors like times of day)?

having different people in each condition (repeated, matched-participant design)
if repeated measures design is used, then this should be counter-balanced. This is where the partic. are split into two groups: group 1 does condition A first then conditions B, while Group 2 does condition B first then A
introduce controls on the experiment to ensure there are as few differences as possible between conditions (e.g. do them in the same room, at the same time, etc)

How can Demand characteristics be controlled?

Single-blind procedure

Advantages and disadvantages of Self-selecting sample?

ADV:
- Consent

Reduces researcher bias

DVNTG:
- more likely to end up with a smaller sample

partic. may share similar personality traits (i.e confident to join in, eager to please) reducing population validity

Advantages and disadvantages of opportunity sampling?

ADV:
- often allows for a larger sample
- more cost-effective

DVNTG:
- researcher bias
- sample could be ethnocentric

Advantages and disadvantages of random sampling?

ADV: - reduces researcher bias - increases population validity DVNTG: - often not possible to have access to the whole target population. - by chance, there can be an imbalance of genders/ages/personalities, reducing population validity.

Advantages and disadvantages of snowball sampling?

ADV: - access to a wider sample, that researchers may not know (increases reliability) ( reduces researcher bias) DVNTG: - participants may only find individuals who are too similar in occupation/ lifestyle, which reduces the reprisentativness of the sample (reduces population validty).

Advantages and disadvantages of working out the MEAN?

ADV: - Takes into consideration all data (nothing is missed out in the calculation) DVNTG: - Can be heavily skewed by outliers (may not represent the general score)

Advantages and disadvantages of working out the MEDIAN?

ADV: - Less affected by extreme scores, so results won't be skewed DVNTG: - Can take very long to calculate if working with a large set of data (results have to be put in order first)

Advantages and disadvantages of working out the MODE?

ADV: - Easy to calculate - Can be used for non-numerical data, e.g what is the average color of a cat? DVNTG: - Impossible to calculate if all the data is different

Advantages and disadvantages of working out the RANGE?

ADV: - quick to calculate --even if using a large data pool-- how dispersed results are DVNTG: - doesn't consider the entire data set - can be skewed by outliers - doesn't give any indication as to whether the spread of scores is evenly distributed (i.e. if there is a cluster of scores towards the top of the data set)

How do you calculate VARIANCE and what is it?

- measure of dispersion that indicates how spread apart the data is within each condition from the average score - 1) calculate the mean score per condition - 2) for each participant, subtract the mean score from their score - 3) square each score - 4) add all the squared numbers together - 5) calculate the mean of these scores added together by dividing by the number of partic. in condition -1

How do you calculate STANDARD DEVIATION?

- square root of the variance

Advantages and disadvantages of VARIANCE?

ADV: - takes account of all the values in a data set, and, as such, it is not affected by outliers o the same extent DVNTG: - figure that is calculated is not expressed in the same units that the data in the original data set is

Advantages and disadvantages of standard deviation?

ADV: - expressed in the same unit as the original data set - takes into consideration the entire data set DVNTG: - time-consuming and more difficult to work out compared to the range score