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

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

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

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.

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.

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%

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

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%

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.

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% Given: 70% Estimated Variability Result; Tolerable Error = +/- 3%; 2 SD of Confidence (95.44%) = 933

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.

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 ==> 45 Given: Range of 3 ==> 45; Tolerable Error = +/- 1; 2 SD of Confidence (95.44%) SD = Range 6 (45 – 3) 6 = = 7 (7) = = 196

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