Random Sampling methods

Question 1

State three types of random sampling methods

Answer 1

Simple random sampling
Stratified random sampling
Systematic random sampling

Question 2

What is simple random sampling

Answer 2

Every sample has an equal chance of being selected.

Question 3

What is the method for simple random sampling

Answer 3

1) Allocate a number between 1 and N to each sampling unit

2) Using random number tables, computer or calculator to select x different number between 1 and N

3) Sampling units corresponding to these number become the sample

Question 4

State three pros of simple random sampling

Answer 4

• it is suitable for small SAMPLES (not large populations)
• simple and easy to implement.
• Each number has a known equal chance of being selected.so BIAS FREE

Question 5

State two cons of simple random sampling

Answer 5

• Not suitable when population size is large.
• sampling frame of the population needed or must assign a number to each member of pop.
• only random if ordered list is truly random

Question 6

What is systematic sampling

Answer 6

Required elements are chosen at regular intervals in ordered list

Question 7

What is the systematic sampling method

Answer 7

Take every kth elements where:

k = pop size (N) / samp size (n)

starting at random item between 1 and 𝑘.

Question 8

State two pros of systematic sample methods

Answer 8

• Simple and quick to use.
• Suitable for large samples/ populations.

Question 9

State two cons of systematic sample methods

Answer 9

• Sampling frame again needed.
• Can introduce bias if sampling frame not random

Question 10

In what instance would systematic sampling not be random

Answer 10

systematic sampling is not random if there are patterns in the data or if the sampling frame is not random

Question 11

What is the stratified sampling method

Answer 11

Population divided into groups (strata) and a simple random sample carried out in each group.

Same proportion (𝑠𝑎𝑚𝑝 𝑠𝑖𝑧𝑒 (𝑛))/(𝑝𝑜𝑝 𝑠𝑖𝑧𝑒 (𝑁) ) sampled from each strata.

Used when sample is large and population naturally divides into groups.

FIRST PERSON MUS BE SELECTED AT RANDOM

Question 12

State two pros of stratified sampling

Answer 12

• Reflects population structure.
• Guarantees proportional representation of groups within the sample

Question 13

State two cons of stratified sampling

Answer 13

• Population must be clearly classified into distinct strata.
• Selection within each stratum suffers from same disadvantages as simple random sampling