Representing data

Question 1

What are the 3 different types of sampling?

Answer 1

• Random sampling
• Systematic sampling
• Opportunity sampling

Question 2

What is random sampling?

Answer 2

Idk how to say it?
- A random sample if size n is a sample of n items/pieces of data taken from a population in such a way that:
All items of the population are equally likely to be chosen
Each possible sample of size n is equally likely to be chosen

Question 3

Positives of random sampling?

Answer 3

• Unbiased ig?

Question 4

Negatives of random sampling?

Answer 4

• Results aren’t certain to be representative e.g. selecting 30 pupils at random from a school but end up with the 30 shortest pupils. Unlikely, but possible O_o

Question 5

What is systematic sampling?

Answer 5

Items are selected from population in a regular pattern, advantage of selected thing spread out throughout population.

e.g.
- Every 50th TV coming off a production line
- Every 100th person from a G.P.’s list

There’s also sampling interval within this, choosing random starting point.
e.g.
Population size N = 400
Sample size = 50
400 / 50 = 8
Choose first point from first 1 - 8 peoples.

Question 6

Positives of systematic sampling?

Answer 6

• Probably also unbiased ig?

Question 7

Negatives of systematic sampling?

Answer 7

• Doesn’t give a random sample as not all samples of a given size are equally likely. Some samples be impossible e.g. impossible to have a sample including consecutive items

Question 8

What is opportunity sampling?

Answer 8

Using items from population which are easily available. Could be obtained by asking members of the population of interest if they would take part in your research.

e.g.
Someone investigating shopping habits might collect data from the first twenty people coming out of a supermarket who were willing to participate in their survey.

Question 9

Positives of opportunity sampling?

Answer 9

• Easy, quick and economical way to obtain a sample

Question 10

Negatives of opportunity sampling?

Answer 10

• Could be unrepresentative or biased
  e.g. (supermarket investigation)
  1. People who don’t shop = not represented
  2. People who shop at different times = not represented
  3. Some may refuse to answer = self-selecting sample
  4. Researcher might be biased themselves by wanting to ask for a certain type of individual based on their race, gender n shi

Question 11

Write down how to do a systematic sampling

Answer 11

Ye k

Question 12

I feel like there’s more here but, mehhhh I’m going on correlation and regression

Answer 12

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