1. Monitoring and Evaluation in the GMS Learning Program 7 – 18 May 2012, Mekong Institute, Khon Kaen, Thailand Randy S. Balaoro, CE, MM, PMP Data Sampling How to determine sample size sample data

2. Monitoring and Evaluation in the GMS Learning Program 7 – 18 May 2012, Mekong Institute, Khon Kaen, Thailand Randy S. Balaoro, CE, MM, PMP Monitoring & Evaluation Processes Mid-term Evaluation Completion Evaluation Outcome Evaluation Impact Evaluation Project Start Design Summary Indicators & Targets Monitoring Mechanism Assumptions & Risks Data Gathering Survey or Observation Analyze Data Recommendation or Conclusion Prepare Report Design and Monitoring Framework

3. Monitoring and Evaluation in the GMS Learning Program 7 – 18 May 2012, Mekong Institute, Khon Kaen, Thailand Randy S. Balaoro, CE, MM, PMP Sampling A way of narrowing down the number of representative subset of a population to make data collection manageable and affordable. 1Random SamplingSelecting respondents randomly like lottery or skip counting. 2Stratified SamplingSelecting respondents based on a defined grouping 3Cluster SamplingSelecting respondents based on some similarities

4. Monitoring and Evaluation in the GMS Learning Program 7 – 18 May 2012, Mekong Institute, Khon Kaen, Thailand Randy S. Balaoro, CE, MM, PMP Census vs Sampling CENSUS = Consider everything, i.e. 100% verification. SAMPLE = Consider a representative group, i.e. relatively less than 100%, and assume that what you don’t check is similar in kind or proportion. When looking for TRENDS in data series and Precision/Accuracy is NOT essential, the best way to get results is by a Sample.

5. Monitoring and Evaluation in the GMS Learning Program 7 – 18 May 2012, Mekong Institute, Khon Kaen, Thailand Randy S. Balaoro, CE, MM, PMP Sampling Rule of Thumb As a general rule-of-thumb, statistical techniques can usually be applied effectively when at least 30 measurements are obtained at random. CAUTION: However, in many project management situations, 30 responses may be insufficient for presenting findings with the degree of confidence and accuracy required.

6. Monitoring and Evaluation in the GMS Learning Program 7 – 18 May 2012, Mekong Institute, Khon Kaen, Thailand Randy S. Balaoro, CE, MM, PMP Criteria for Determining Sample Size CriteriaDefinitionSample Value VariabilityExtent of variation in the population to be studied 65% or a value of range Tolerable ErrorThe amount of error that management is willing to accept in the findings ± 5% or ± 10 Confidence LevelThe level of assurance that the results are accurate when presenting the findings 1 SD = 68.2% 2 SD = 95.44% 3 SD = 99.74%

7. Monitoring and Evaluation in the GMS Learning Program 7 – 18 May 2012, Mekong Institute, Khon Kaen, Thailand Randy S. Balaoro, CE, MM, PMP 100 90 80 70 60 50 40 30 20 10 0 σ σ A data set with a mean of 50 and a standard deviation (σ) of 20 Understanding Standard Deviation (σ)

8. Monitoring and Evaluation in the GMS Learning Program 7 – 18 May 2012, Mekong Institute, Khon Kaen, Thailand Randy S. Balaoro, CE, MM, PMP Understanding Standard Deviation (σ) 1σ2σ 3σ-1σ-2σ-3σμ 34.1% 13.6% 2.1% 1 SD = 68.2% 2 SD = 95.44% 3 SD = 99.74% 1SD = 68.02% 2SD = 95.44% 3SD = 99.74%

9. Monitoring and Evaluation in the GMS Learning Program 7 – 18 May 2012, Mekong Institute, Khon Kaen, Thailand Randy S. Balaoro, CE, MM, PMP Appropriate Sample Size (%) Sample Size = (100 – Estimated %) x Estimated % Error Confidence 2 NOTE: When you have absolutely no idea of the percentage the result is likely to be, use 50% because this will give the largest sample size – i.e. an over- sampling -- but still better than an inadequate sample.

10. Monitoring and Evaluation in the GMS Learning Program 7 – 18 May 2012, Mekong Institute, Khon Kaen, Thailand Randy S. Balaoro, CE, MM, PMP Appropriate Sample Size (%) Sample Size = (100 – 70%) x 70% 3 2 2 Given: 70% Estimated Variability Result; Tolerable Error = +/- 3%; 2 SD of Confidence (95.44%) = 933

11. Monitoring and Evaluation in the GMS Learning Program 7 – 18 May 2012, Mekong Institute, Khon Kaen, Thailand Randy S. Balaoro, CE, MM, PMP Appropriate Sample Size (Average) Sample Size = Standard Deviation Error Confidence 2 2 NOTE: Averages are still important for describing and evaluating the indicators of many variables even though they are not “Best Practices” for targeting.

12. Monitoring and Evaluation in the GMS Learning Program 7 – 18 May 2012, Mekong Institute, Khon Kaen, Thailand Randy S. Balaoro, CE, MM, PMP Appropriate Sample Size (Average) Sample Size = Standard Deviation Error Confidence 2 2 3 ==> 45 Given: Range of 3 ==> 45; Tolerable Error = +/- 1; 2 SD of Confidence (95.44%) SD = Range 6 (45 – 3) 6 = = 7 (7) 3 2 2 2 = = 196

13. Monitoring and Evaluation in the GMS Learning Program 7 – 18 May 2012, Mekong Institute, Khon Kaen, Thailand Randy S. Balaoro, CE, MM, PMP The End