Research Methods Flashcards
What is random sampling? + Evaluation
Participants are picked out of a target population using either a number generator or name-out-of-hat method.
Evaluation:
- Free from researcher bias
- Time-consuming
- Representive sample is not guaranteed (some sub-groups may be overrepresented or not selected)
What is stratified sampling? + Evaluation
Target population divided into strata (groups). From each strata participants are randomly selected.
Evaluation:
- Avoids researcher bias
- May lack 100% representation
What is systematic sampling? + Evaluation
Pick every nth participant from target population.
Evaluation:
- Free from researcher bias
- Creats a fairly representive sample
What is volunteer sampling? + Evaluation
This is when the participants put themselves forward i.e. they self-select. The researcher places an advert in a newspaper or magazine or on a public noticeboard.
Evalutation:
- Requires minimal input from researchers
- Introduces demand characteristics
- Participants will be engaged
- Volunteer bias
What is an opportunity sample? + Evaluation
Opportunity sampling is where a researcher selects participants based on their availability. One example would be standing on the street asking passers by to join the research.
Evaluation:
- Convenient
- Time-effective
- Less costly
- Unrepresentative of the target population
- Suffers from researcher bias
What are lab experiments?
Lab experiments take place in controlled environments.
What is a structured interview?
Where there is a set list of questions that is not deviated from.
What is a semi-structured interview?
Where there is a list of questions but the interviewer is free to add supplementary questions, leave questions out or follow interesting lines of inquiry.
What is an unstructured interview?
There are no pre-set questions, just a free-flowing conversation. The researcher would have some themes or headings to work with, but otherwise, the discussion could go anywhere.
What are the 4 types of observations?
- Participant (the researcher plays an active part)
- Non-participant (the researcher simply observes)
- Overt (everyone is aware the observation is taking place)
- Covert (the people being observed are not aware the observation is taking place)
Define directional hypotheses and when they would be used?
A directional hypothesis is a hypothesis that predicts an outcome or direction of the relationship between variables.
It would be used when there is previous research available which informs the researcher of the expected direction of the result.
Define non-directional hypotheses and when they would be used
A non-directional hypothesis is a hypothesis that does not state the direction of the outcome.
It is used when there is no prior research in the topic or present research is contradictory. It states a relationship but not the expected direction of the results.
Define operational hypotheses
Operational hypotheses predict exactly the outcome.
What is the mean and how do you work it out?
The mean is a measure of central tendency in statistics. It gives you an average value that represents the “typical” value in the data set.
To calculate the mean, you add up all the values in a set of data and then divide the sum by the total number of values.
The mean may not be the best choice sometimes as it is affected by outliers in the data set.
What is the median and how do you work it out?
The median is another measure of central tendency. To find the median, you arrange the values in a data set in ascending or descending order and then find the middle value. The median represents the value that separates the higher and lower halves of the data. If there is an even number of values, you take the average of the two middle values. For example:
2, 4, 6, 8, 10, 12, the middle two values would be 6 and 8. Therefore, the average would be 7.
What is the independent variable?
What you change
What is the dependent variable?
What you measure/observe
What is the control variable?
What you keep the same
what are the 3 experimental designs?
- independent groups
- repeated measures
- matched pairs
describe independent groups
2 separate groups experience 2 different conditions
describe repeated measures
all participants experience both conditions
describe matched pairs
participants paired together on a variable/variables relevant to the experiment
what are strengths of independent groups?
- order effects aren’t a problem
- participants less likely to guess aim
what are limitations of independent groups?
- independent differences acting as a confounding variable meaning validity is reduced ➜ random allocation fixes this
- less economical as each participant contributes a single result meaning increased time/money on recruiting participants