AS Lessons 06 - 10 Flashcards
Target population
The group who researchers are studying and want to generalise their results to
Sample
A sample should be representative of the population from which it is drawn and should therefore have the same characteristics as the population
Random Sampling
When every member of the target population has the same chances of being selected. The best way is to place all names in a hat and select the sample
Evaluation of Random Sampling
+ If the target population is large and a large sample is drawn, then it is likely that the sample will be representative and therefore the results can be generalised
+ No researcher bias - the sample has been chosen by chance without any conscious choice
- Sometimes difficult to get full details of a target population (e.g. not possible to get the names of all women aged 20-30)
- Not all members of the target population who are selected are available or willing to take part, making the sample unreliable
Systematic Sampling
A sampling strategy where participants are selected by taking every Nth person from a list. For example, make a list of the total population and then select every 6th person to take part
Evaluation of Systematic Sampling
+ Far more simple than random sampling as it only requires a list, and then the researcher decides every Nth person. Random sampling requires more time and effort (put the names in a hat etc.)
- Process of selection can interact with a hidden periodic trait. If they do coincide, the sampling technique will no longer be random
- Not all selected participants will be available or willing to take part, making the sample unrepresentative
Stratified Sampling
Involves classifying the population into categories and then randomly choosing a sample which consists of participants from each category in the same proportions that they are in the population. The population are divided into ‘strata’ in terms of characteristics (e.g. age, gender etc.). A sample is then chosen that reflects these characteristics (e.g. 51% female, 49% male)
Stratified samples ensure the sample is representative
Evaluation of Stratified Sampling
+ All groups within a population are included, so the sample is representative of the population
- Can be very time consuming as the categories have to be identified and calculated. If you do not have details of all the people, you would struggle to conduct a stratified sample
Opportunity Sampling
AKA convenience sampling
Involves selecting participants who are readily available and willing to take part. Psychologists may have easy access to a group of people, so it would be convenient to ask them to take part
Evaluation of Opportunity Sampling
+ Easiest and most practical method of ensuring large samples especially when compared to stratified sampling, which is time consuming and expense
- High chance that the sample will not be representative of the target population. Sometimes people feel obliged to take part (especially when a friend asks them to), even if they do not want to, making it unethical
Volunteer Sampling
Involves people volunteering to participate. The researcher will usually ask people to take part, possibly through advertisement (leaflets, posters, radio or TV broadcasts). These forms of communication means that people take notice of the information and then decide if they want to take part
Evaluation of Volunteer Sampling
+ Saves the researcher time and effort. The researcher needs to construct an advertisement for the study, and then just needs to wait. This is better than other sampling methods where the researcher needs to ask people to take part and needs their full commitment
- A certain type of person tends to volunteer (enthusiastic, interested in the topic etc.), which means that there is a high chance of the sample being unrepresentative and it will not accurately reflect the target population (volunteer bias)
Pilot Studies
An initial run-through of the procedures. It involves selecting a few people and trying the study out on them. It saves time and possibly money, by identifying flaws early on. It can help identify any ambiguities or confusion. Sometimes the task is too hard and the researcher may get a floor effect, because none of the participants can complete the task. The opposite is a ceiling effect, where the task is too easy and full marks are achieved a lot.
Evaluation of Pilot Studies
+ A chance to make modifications and amendments
+ Good in the long run as it saves time and money
- Can be time consuming
- As it is small scale, the results may be unrepresentative
- The sample cannot be repeated - these people cannot take part again
Experimental Designs
How participants are organised within an experiment
Types of Experimental Designs
Independent groups
Repeated measures
Matched pairs
Experimental Condition
Involves a group of people who are exposed to the independent variable
Control condition
This group receives no treatment and are used as a base line to compare results
Randomisation
The use of chance in order to control for the effects of bias when deciding the order of conditions.
Example: putting words in a random order to make sure a list of words is not too easy or too hard
Standardisation
Using exactly the same formalised procedures and instructions for all participants - this improves the reliability of the study (the ability to repeat and get the same findings)
Random allocation
An attempt to control for participant variables in an independent groups design which ensures that each participant has the same chance of being in one condition or the other
Independent Groups Design
Different participants are used in each condition, therefore the groups are independent from one another. Participants are randomly allocated to each condition
Evaluation of Independent Groups Design
+ Order effects (when the sequence in which the participants take part in conditions influence their performance) will not occur as there are different participants. For example, in a memory test, participants may get better with practice.
+ The chance of demand characteristics is reduced as there are different participants for each condition. There is a lower chance of them guessing the aim
+ Participants are not lost between conditions as they only take part in one condition. In a repeated measures design, participants are used for two conditions, so there is a higher chance of participants leaving (being lost)
- More participants are needed compared to a repeated measures design.
- There is a chance that the different results gained are due to individual differences rather than manipulation of the IV, because two separate groups are used
Repeated Measures Design
Each participant is tested in all conditions