Sampling is extremely important when carrying out experiments. There are numerous types of sampling techniques, all of which are used based according to the type of study and sample the researcher wants to direct the study at. Below are some example of sampling.
random sampling
Everyone in the target population has an equal chance of being chosen to take part in the study.
opportunity sampling
The sample consists of people present there at the time.
systematic sampling
Participants are chosen in a systematic way. For example, every 5th person who enters the room.
Self selected sampling
Participants volunteer to take part in the study. This may be by answering an advert or email.
stratified sampling
This involves dividing the target population into groups. The sample size for each group is equivalent to the proportion of the group participants represent. e.g. selecting samples from different age groups.
Relationships between researcher and participant
This is about the way in which the researcher or even participants can influence the results and outcome of the study.
Researcher effects: The researcher may affect the results of the study by affecting the behaviour of the participants. One example being the researcher may unknowingly express his expectations to the participants. Another example includes the researcher unknowingly interpreting the data the way they would like to find.
Participant demand characteristics is an example of how the researcher may affect the behaviour of participants. For instance, they may change their behaviour accordingly. Furthermore, the participants may not want to show certain behaviours which they may keep hidden from the researcher.
Researcher effects: The researcher may affect the results of the study by affecting the behaviour of the participants. One example being the researcher may unknowingly express his expectations to the participants. Another example includes the researcher unknowingly interpreting the data the way they would like to find.
Participant demand characteristics is an example of how the researcher may affect the behaviour of participants. For instance, they may change their behaviour accordingly. Furthermore, the participants may not want to show certain behaviours which they may keep hidden from the researcher.
Minimising researcher effects and demand characteristics
There are numerous ways in which the researcher can reduce reducer effects and participant demand characteristics. Some of which are:
Disguise the purpose of the investigation,
Single blind design - participants are unaware of the condition in which they are in
Double blind design - the researcher and participants are unaware of the condition participants are placed in.
Disguise the purpose of the investigation,
Single blind design - participants are unaware of the condition in which they are in
Double blind design - the researcher and participants are unaware of the condition participants are placed in.