Sampling

Question 1

Population

Answer 1

The large group of people that a researcher is interested in studying.

Question 2

Sample

Answer 2

As it would usually not be possible to include all members of the target population in the study, a smaller group is selected, the sample

Question 3

Generalisation

Answer 3

The sample that is drawn should be representative of the population so generalisations can be made

Question 4

Bias

Answer 4

Most samples are biased because a certain group may be over or under represented

Question 5

Random sample

Answer 5

Everyone in the target population has an equal chance of being selected. Using the lottery method, all members of the target population are given a number and a number randomiser can randomly selected someone, or names can be drawn from a container

Question 6

Systematic sample

Answer 6

An organised list of the target population e.g. names in alphabetical order and then every nth person from the organised list is selected

Question 7

Stratified sample

Answer 7

The sample reflects proportions of people in certain subgroups within a population. Subgroups identified then relative percentages of the subgroups within the population are calculated. Then participants randomly selected until you have the right amount of participants from each subgroups. e.g. if 80% of the target population are under 19 then 80% if the sample should be under 19, so if the sample consists of 50 students, 40 should be under 19.

Question 8

Opportunity sample

Answer 8

The people who are most available at the time. Ask people nearby to take part in your experiment

Question 9

Volunteer sample

Answer 9

Participants selected themselves. This can be done by them following an advert for an experiment or putting their hand up when someone asks for volunteers