1
Q
types of experiments
A
- labratory experiment
- field experiment
- quasi experiment
2
Q
labratory experiment
A
- the IV is manipulated by the researcher
- the experiment is carried out in a labratory or other highly controlled setting away from the particiants noral environment
3
Q
advantage of labratory experiment
A
- high control of extraneous variables therefore increasing confidence that the IV effected the DV (known as the cause and effect)
- standardised procedures and instructions are used which enables researchers to repeat the study in the exact same way with other participants which increases internal reliability
4
Q
weakness of labratory experiments
A
- the unnatural/artificial situation of a lab may mean that participants do not display behaviour that reflects how they would behave in real life which decreases ecological validity
- due to having a researcher present, participants may suffer with demand characteristics. This means that they behave in a way that would please the experiment which means that the participants are not behaving in a true way lowers ecological validity
5
Q
field experiment
A
- the iv is manipulated by the researcher
- carried out using participants normal surroundings
6
Q
strength of field experiments
A
- as participants are in their normal environment/situation, their behaviour is likely to be more valid as it will reflect their true behaviour
- participants may be unaware that they are being studied and therefore less effected by demand characteristics
- controlled setting meaning that ecological validity is high so it can be generalised to real life scenarios.
7
Q
weakness of field experiment
A
- Control over extraneous variables is more difficult because the situational extraneous variables are difficult to control. This can make them less reliable and difficult to replicate in a standardised way.
- The researcher cannot be sure that the IV caused the effect on DV. This is due to the lack of control over the environment.
- Participants could be unaware that they are being studied as many field experiments are in natural environments such as supermarkets, schools etc. This raises ethical issues.
8
Q
quasi experiment
A
- the IV is naturally occurring not manipulated by the researcher
9
Q
strength of quasi experiment
A
- Due to the IV naturally occurring within the individual it may be more reflective to that individual.
- They allow researchers to investigate variables that would be unethical to manipulate
10
Q
weakness of quasi experiment
A
- Control over extraneous variables is often difficult. As the researcher is not manipulating the IV, they can be less sure that it caused an EFFECT on the DV.
- They are generally hard to replicate and therefore can lack internal and external reliability.
11
Q
tagret population
A
the set of people researchers want to find out about
12
Q
sample
A
a small set of people taken from the target population
13
Q
representative
A
how well a sample reflects the target population
14
Q
gender bias
A
sample is made of people from one gender, not representative of all genders
15
Q
androcentric
A
a sample that contains a large population of males
16
Q
gynocentric
A
a sample that contains a large proportion of females
17
Q
cultural bias
A
sample is too focused on one culture, it isnt representative of all cultures
18
Q
ethnocentric
A
the research only focuses on one culture
19
Q
experimental designs
A
- repeated measures design
- independent measures design
- matched participant design
20
Q
single blind test
A
- when the participants are unaware of the condition that they are in.
- This means 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. Therefore reducing demand characteristics.
21
Q
double blind test
A
- neither the researcher or the participants are aware of which condition an individual is in.
- This ensures that demand characteristics are reduced from the participants, but also researcher bias is also reduced.
22
Q
extraneous variables
A
- situational variables
- design variables
- participant variables
23
Q
situational variables/effects
A
- things that could effect participants behaviour in the environment, such as lighting, sound, temperature.
24
Q
design variables
A
- things like order effects, fatigue effects i.e. tiredness by carrying out a repeated measures design. For a independent measures design, you have the issue of comparing two different groups of people, so there will be participant variables
25
participant variables/effects
are things like mood, intelligence. Things about the participant that may effect their behaviour in the study.
26
independent measures design
- using different people in each condition
27
strengths of independent measures design
- Different participants are used in each condition, so there are no practice effects.
- Participants only see the experimental task once, meaning that they are less likely to guess the aims of the study and change their behaviour as a result. For example the participant may work out that the researchers are trying to see if the number of people effect sport performance and then change their behaviour to fit in with their expectations – thus reducing validity.
- as the participant in each condition are unaware of the other, they will show reduced demand characteristics
- no order effects as only take part on one condition
28
weakness of indepedent measures
- Individual differences could act as an extraneous variable and make it look like the IV effected the DV, but in fact it was something about the individual.
- More participants are needed, so maybe more difficult to find.
- Although demand characteristics are reduced in a independent measures design. It can be further be improved by carrying out a single blind or a double blind procedure.
29
repeated measures design
- using the same people in each condition
30
strengths of repeated measure design
- Individual differences are unlikely to distort the effect of the IV on the DV, as participants do both levels.
- Uses fewer participants, so maybe easier to collect.
- If counterbalancing is used, this can reduce order effects as outlined in the evaluation of independent measures design.
31
weakness of repeated measures
- Order effects such as practice and fatigue effects i.e. participants get bored of doing the same thing and so do not contribute a valid reflection of their behaviour.
- Participants see the experimental task more than once meaning they are more likely to guess the aim, and therefore more likely to suffer from demand characteristics.
32
matched participant design
- involves using different people in each condition but an attempt to make the participant as similar as possible on certain key characteristics
33
strengths of a matched participant design
- Different participants are used in each condition, so there are no order effects
- Participants only see the experimental task once, meaning that they are less likely to guess the aims of the study, and therefore reduce demand characteristics.
- The effects of individual differences are highly controlled, so less chance of participant extraneous variables.
34
weakness of matched participant design
- matched participants in each condition may be limited. This is because it is difficult to ensure that the matching is completely accurate, as other variables about the participant may be unknown.
- Matching participants can be very time consuming and difficult.
35
how to control participant variables
- either have the same people in each condition (repeated measure design) or similar people in each condition (matched participant design)
- Assign participants randomly to groups to make sure their characteristics are spread out evenly.
36
how to control situational variables/effects
- having different people in each condition will avoid this which would be a benefit of using either an independent measures design or a matched participant design
- if repeated measures design is used, the same people are taking part then this should be counter-balanced
(this is where participants are split into 2 groups, group 1 does condition A first then condition B while group 2 does condition B first and then condition A.
37
how to control design/environment variables
- impose controls on the experiment to ensure that there are as few differences as possible between the 2 conditions
38
how to control demand characteristics
- do not tell the participants the aim of the investigation
- use a single blind procedure
39
alternative hypothesis
- predicts how the IV is likey to affect the DV
40
null hypothesis
- predicts that the IV will not have an effect on the DV
- predicts that any difference seen will be due to chance factors rather than IVs.
- e.g. *"There will **not**be a **significant difference** in the number of balls successfully thrown into a bucket when completing the task in front of a noisy audience as opposed to a silent audience; **any difference will be due to chance factors**"*
41
two-tailed hypothesis
- predicts that the **IV will have a significant effect on the DV**
- *does **not** have a **direction** *
- e.g. *Eating chocolate will have an EFFECT on mood (measured on a scale of 1-10, 1 being very sad, and 10 being very happy, how do you feel?) when eating a bar of chocolate compared to not eating chocolate.*
42
one tailed hypothesis
- This predicts that the IV will have a significant effect on the DV
- predicts the **direction** this effect will go in.
e.g. *Eating chocolate will have a positive EFFECT on mood (measured on a scale of 1-10, 1 being very sad, and 10 being very happy, how do you feel?) when eating a bar of chocolate compared to not eating chocolate*.
43
opportunity sampling
- a sample of participants produced by slecting those who are most readily available at a given time and placed selected by the researcher
44
strengths of opportunity sampling
- Quick and easy to carry out. This is because it relies on people who are around at the time. This is a strength as it is very easy to replicate and is far more time efficient than other sampling methods.
- Can help to collect participants with similar characteristics as people who share characteristics tend to seperate into the same areas. This is a strength because it helps to accurately generalise findings to a target population.
45
weakness of opportunity sampling
- Not representative as the kinds of people available are likely to be limited, and therefore similar, this makes the sample difficult to generalise to the wider population.
- Increased chance of researcher bias as they may only approach people who they feel will give them the results they want.
46
self-selecting sample
when people volunteer to take part in the study; often through adverts, leaflets
47
strength of self-selected sampling
- Relatively easy as the participants come to you. This is a strength becuase they have volunteered they are likely to remain comitted to the study and less likely to drop out, preventing the chance of a small, unrepresentative sample.
- Can reach a wider variety of participants through emails, posters, advertisements compared to opportunity sample, which will only cover a small area.
48
weakness of self-selected sample
- Sample Bias, usually there are certain individuals that volunteer for studies and therefore may not be representative of all people. Therefore, the results would not be valid when generalising to people who do exercise.
- Sometimes there will not be enough interest in your studies advert which can lead to a small sample. This is a weakness as it could lead to an unrepresentative sample.
49
snowball sampling
when participants are asked to contact their friends and family to ask them to also take part in the research and they in turn then ask other people
50
strengths of snowball sampling
- Quick and easy to carry out as you only have to find a few participants, then they find the rest for you.
- It is a convenient way to find a sample with certain characteristics as friends are likely to be similar therefore representative to the target population
51
weakness of snowball sampling
- Sample Bias due to having similar characteristics/culture as they all friends, therefore less generalisable
- More chance of social desirability if all participants are friends with each other. This would decrease the validity of the results.
52
random sampling
- each member of the target population has an equal chance of being selected
53
strength of random sampling
- The most representative sampling technique to use as all types of people in the population are equally likely to be chosen.
- Provides unbiased sample as the researcher has no part in deciding who is selected, therefore reduces the chance of researcher bias, increasing validity.
54
weakness of random sampling
- Time consuming and hard to ensure that everyone is equally chosen e.g. due to lack of infomation or access.
- Sample could still be biased e.g. if only girls happen to be selected, this would create a gynocentic sample that lacks generalisability.
UNIT 1 PSYCHOLOGY
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