0
Part Two      THE DESIGN OF RESEARCH7-1
Chapter Seven      SAMPLING DESIGN7-2
Selection of Elements      • Population      • Population Element      • Sampling      • Census7-3
What is a Good Sample?      • Accurate: absence of bias      • Precise estimate: sampling error7-4
Types of Sampling Designs      • Probability      • Nonprobability7-5
Steps in Sampling Design      •   What is the relevant population?      •   What are the parameters of interest?      •   ...
Concepts to Help Understand               Probability Sampling      • Standard error      • Confidence interval      • Cen...
Probability Sampling Designs      • Simple random sampling      • Systematic sampling      • Stratified sampling        – ...
Designing Cluster Samples      • How homogeneous are the clusters?      • Shall we seek equal or unequal clusters?      • ...
Nonprobability Sampling       Reasons to use       • Procedure satisfactorily meets the sampling         objectives       ...
Nonprobability Sampling       • Convenience Sampling       • Purposive Sampling         – Judgment Sampling         – Quot...
Upcoming SlideShare
Loading in...5
×

Rm7 sampling design

837

Published on

Published in: Education
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
837
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
28
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide

Transcript of "Rm7 sampling design"

  1. 1. Part Two THE DESIGN OF RESEARCH7-1
  2. 2. Chapter Seven SAMPLING DESIGN7-2
  3. 3. Selection of Elements • Population • Population Element • Sampling • Census7-3
  4. 4. What is a Good Sample? • Accurate: absence of bias • Precise estimate: sampling error7-4
  5. 5. Types of Sampling Designs • Probability • Nonprobability7-5
  6. 6. Steps in Sampling Design • What is the relevant population? • What are the parameters of interest? • What is the sampling frame? • What is the type of sample? • What size sample is needed? • How much will it cost?7-6
  7. 7. Concepts to Help Understand Probability Sampling • Standard error • Confidence interval • Central limit theorem7-7
  8. 8. Probability Sampling Designs • Simple random sampling • Systematic sampling • Stratified sampling – Proportionate – Disproportionate • Cluster sampling • Double sampling7-8
  9. 9. Designing Cluster Samples • How homogeneous are the clusters? • Shall we seek equal or unequal clusters? • How large a cluster shall we take? • Shall we use a single-stage or multistage cluster? • How large a sample is needed?7-9
  10. 10. Nonprobability Sampling Reasons to use • Procedure satisfactorily meets the sampling objectives • Lower Cost • Limited Time • Not as much human error as selecting a completely random sample • Total list population not available7-10
  11. 11. Nonprobability Sampling • Convenience Sampling • Purposive Sampling – Judgment Sampling – Quota Sampling • Snowball Sampling7-11
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×