Types of Sampling

Question 1

Random Sampling

Answer 1

Definition: Every member of the population has an equal chance of being selected.

Advantage: Reduces bias.

Disadvantage: May not be representative.

Question 2

Stratified Sampling

Answer 2

Definition: Population is divided into groups (strata), and a proportional sample is taken from each.

Example: Age groups, genders.

Advantage: More representative.

Question 3

Systematic Sampling

Answer 3

Definition: Selects every nth person from a list.

Example: Every 5th person in a register.

Advantage: Easy to use.

Disadvantage: May still miss patterns in data.

Question 4

Opportunity Sampling

Answer 4

Definition: Using people who are easy to access.

Example: Asking your classmates.

Advantage: Quick and easy.

Disadvantage: Can be biased.

Question 5

Census

Answer 5

Definition: Collecting data from every member of the population.

Advantage: Very accurate.

Disadvantage: Time-consuming and expensive.

Question 6

Quota Sampling

Answer 6

Definition: Researcher picks participants to meet quotas for different groups.

Advantage: Quick and easy.

Disadvantage: Can be biased (non-random selection).

Question 7

What is a pilot survey?

Answer 7

A small trial run of a survey to test questions and methods before the main survey.

Good because:
Identifies problems early
Saves time and money
Improves reliability

Question 8

Petersen Capture - Recapture Formula

Answer 8

N/M=n/m

M=total tagged at start
N=population (unknown)
m=number tagged in sample
n=sample size