16. STRATIFIED RANDOM SAMPLING

Question 1

1. What method does Stratified Random Sampling have the same principles as?

Answer 1

• Simple Random Sampling

Question 2

2. What is different when it comes to Stratified Random Sampling?

Answer 2

• the sampling is done within Strata
• these are subgroups of the population
• these groups revolve around key demographic
  characteristics

Question 3

3. What should the size of the random sample be proportional to?

Answer 3

• the size of the Random Sample should be proportional
  to the specific stratum size in the population

Question 4

4. Does this example make sense?

Answer 4

• yes

Question 5

5. What are the 6 steps the Stratified Random Sampling procedure?

Answer 5

1. Identify the source population
2. Set up the Sampling Frame
3. Decide on the Sample Size
4. Decide on the Pre-defined Population Strata
5. Based on the overall proportions of the population:
   - you can calculate how many people should be
   sampled from each subgroup
6. Randomly select the individuals to fill the strata

Question 6

6. Does this image make sense?

Answer 6

• yes

Question 7

7. Does this example make sense?

Answer 7

• yes

Question 8

8. Does this example make sense?

Answer 8

• yes

Question 9

9. What are the 2 advantages of the Stratified Random Sampling Procedure?

Answer 9

1. IT ALLOWS YOU
   - to draw more precise conclusions
   - by ensuring that every subgroup is properly
   represented in the sample
2. IT ENABLES US TO
   - compare the sub-groups of the population

Question 10

10. What are the 2 disadvantages of the Stratified Random Sampling Procedure?

Answer 10

1. IT IS MORE TIME CONSUMING
   - than the Simple Random Sampling procedure
2. IT HAS A HIGHER COMPLEXITY
   - this may give rise to errors
   - the stratification may not be conducted properly