Experimental Methods Flashcards
Types of experiment
Field, Natural, Quasi, Lab
What is field experiment
Strength and limitation
Take place in a participants usual environment. Participants tend not to be aware that they are taking part in this type of experiment. IV is still deliberately manipulated by the researcher.
Example - if investigating whether people obey authority figures, we could dress in different ways, stand outside a railway station, drop a piece of litter and tell a passerby to ‘pick it up’. We can try this in different outfits ie. milkman, policeman or everyday clothes.
Strengths: Behaviour of participants likely to be natural, reduced chance of demand characteristics
Weaknesses: Difficult to replicate, cause and effect more difficult to determine as not all EVs controlled
What is a Lab experiment
Strength and limitation
A controlled environment where EVs and CVs can be regulated. Participants go to the researcher, The IV is deliberately manipulated and the DV is recorded.
Strengths: Cause and effect can be determined due to control of CVs and EVs
Can be more easily replicated
Weaknesses: May lack generalisability as behaviour may be artificial
Demand characteristics may be an issue - participants guessing the aim
What is a natural experiment
Strength and limitation
IV occurs naturally and is not deliberately manipulated by the researcher. It is usually a natural event. Participants tend not not be aware they are taking part in this experiment.
Example - a natural experiment was conducted in St Helena to see whether the introduction of TV would provide an increase in anti-social behaviour. They received TV for the first time in 1995. The found no difference in anti social behaviour before and after its introduction. The IV (the introduction of TV) was a natural event.
Strengths: Participants behaviour likely natural as being studied in their usual environments. Also reduced likelihood of demand characteristics as not usually aware they are being tested.
Weaknesses: Tend to be difficult if not impossible to replicate due to the lack of level of control.
Cause and effect cannot be determined as EVs not controlled.
What is a quasi experiment
Strength and limitation
The IV is not deliberately manipulated by the experimenter but occurs naturally. Usually takes place in a lab so some control of EVs.
Example - if researchers want to see if male and female students use different revision techniques. The IV (gender) is fixed and not manipulated.
Strengths: Allows investigation of situations that are not normally possible
Weakness: Cause and effect more difficult to determine as not all EVs controlled
Difference between Extraneous variable and confounding variable
Types of extraneous/confounding variable
Participant variables - are related to the participants involved. Only an issue when the same participants are used in each condition. For example, might be age, gender, intelligence
Situational variables - any EVs/CVs related to the research situation that might influence participant behaviour. Ie noise, time of day
Demand characteristics - can occur when participants are very conscious about taking part in research and thy become curious about what they are being asked to do. They might look for clues on how they are expected to behave and produce the behaviours that they believe the researcher is demanding.
Investigator effects - anything a researcher does that has an effect on a participant’s performance in a study other than what was intended. Ie they might unintentionally communicate with the participants either verbally or non verbally or in the way the study is designed.
Order effects - Refers to the order in which participants in conditions when a repeated measures design is used. ie improved performance in the second condition could be due to practice. They could also do less well in the second condition due to boredom or fatigue.
How to know what type of experiment is being used
How to counteract different types of extraneous/confounding variables
Situational variables - standardisation - involves keeping everything other than the IV the same between conditions. ie. participants given the same instructions all conditions, using the same room and researcher for both conditions etc
Participant variables - random allocation - participants are allocated to each condition on a random basis
Order effects - Randomisation - can be useful if more than 2 conditions. Participants complete all conditions in a random order ie by placing numbers in a hat to represent each condition and each participant pulls out a number
Also counterbalancing - if there are 2 conditions half the participants do condition A then B, the other half do B then A
Investigator effects - also random allocation.
Demand characteristics - single blind design - here participants are not made aware of the research aim or which experimental condition they have been placed in. This reduced the chances of them changing their behaviour to match what the think is expected of them.
What are descriptive statistics
Measures of central tendency and measures of dispersion. They provide a summary of quantitive data.
What are measures of dispersion
Strengths and limitations
Provide information about how the values in a set of data are spread out
Range - distance between the top and bottom values in a set of data
Strength: Can calculated the basic indication of a spread of scores on most types of data
Weakness: Can be distorted by extreme scores
Standard Deviation - Measure of the spread of scores around the mean and commonly calculated alongside the mean
Strength: Most accurate measure of dispersion as it takes each exact value into account
Weakness: Can be difficult to calculate
What are experimental designs and strengths and limitations of these
What are measures of central tendency?
Strengths and weaknesses of each
Mean - all values are added together and divided by the total number of values
Strength: Most sensitive measure of central tendency - uses all scores in data set, the mean value is representative of all scores and not a select few
Weakness: Can be easily distorted by few extreme scores
Median - When all values are arranged in order, the middle value is the median
Strength: Not affected by extreme score so can be representative under such circumstances
Weakness: Is not as sensitive as the mean as it does not take all data into account
Mode: Most frequently occurring value in a set of data
Strength: not affected by extreme score
Can be used with all types of data
Weakness: Does not take all scores into account
Not useful when many or no modes
