Ver 10.0 September 29, 2005

1. DoD Counterintelligence STRATEGY MAPPING William L. McCoy Senior Program Manager Lockheed Martin Integrated Technology Ver 10.0 September 29, 2005

2. STRATEGY MAPPING OBJECTIVE To develop a methodology that defensibly and quantitatively maps the DoD CI Strategy (and eventually DoD CI resources to achieve it) to DNI Strategic Objectives, NCIX Pillars, Defense Intelligence Goals, and other guidance documents.

3. BRIEFING OVERVIEW • Purpose:Recommend survey universe, sample size (if required) and analysis methodology for strategic mapping project that maps DoD CI General Goals to: • National Counterintelligence Pillars • Director of National Intelligence Strategic Objectives • USD(I) Defense Intelligence Goals • Discussion: • DT Survey Results • Part 1 – Universe and Sample Size Methodology • Recommendation and Decision • Part 2 – Data Reduction and Analysis • Recommendation and Decision • Next Steps

4. DT SURVEY RESULTS

5. PART 1 UNIVERSE AND SAMPLE SIZE METHODOLOGY

6. SURVEYING • Survey types: • Sample – more involved as we must make corrections for the error introduced by not surveying the universe. Sampling is required if the universe is too large. • Population – more straight forward as no errors are introduced by sampling but requires manageable universe. • Sampling introduces an additional step of determining and • correcting for the variance – hence the arcane statistics. The analysis commences after the numbers are crunched. The results can be accepted at face value or adjusted/revised based on subject knowledge.

7. OPTION DISCRIMINATORS OPERATIONAL DEFINITIONS FOR SURVEY “TERMS OF ART” DISCRIMINATORS

8. UNIVERSE ASSUMPTIONS • OPTION 3 • estimate • CIRROC • Member • Organizations 80 • Total 80 • OPTION 2 • estimates • AF OSI 65 • Navy NCIS 75 • USMC 25 • Army 55 • Agencies 80 • Total 300 • OPTION 1 • estimates • AF OSI 450 • Navy NCIS 700 • USMC 200 • Army 350 • Agencies 300 • Total 2,000 • SAMPLE SIZE • Target population of 2,000 • Confidence interval +/- 5% • Confidence level of .95 • Then sample size = 92 • SAMPLE SIZE • Target population of 300 • Confidence interval +/- 5% • Confidence level of .95 • Then sample size = 73 • SAMPLE SIZE • Target population of80 • 100% survey possible • Then target universe = 100% ASSUMPTIONS OPTION 1: The survey is administered to randomly selected DoD CI leadership and planners down to unit officersand senior NCOs and includes civilians. OPTION 2: Uses OPTION 1 assumption but restricts survey participation to DoD CI leadership, planners, and resource managers down to major unit level. OPTION 3: Limits the survey to National level DoD CI leaders, strategic planners, and resource managers.

9. OPTION 1 DETAIL Assumption: To map CI strategy we need input from all levels of the DoD CI community (OSD, CIFA, Services, Agencies, Regions, Brigades, Groups, Battalions, Detachments, etc.) from DoD CI leadership and planners down to unit CI officers and senior CI NCOs and civilian equivalents. • PROs: • Elicits input from those not normally associated with strategy issues. • Provides an operator perspective on CI strategy. • CONs: • Partially substitutes opinion for judgment. • Includes population with out experience with or insight into National or Defense CI activities. • Risk of missing significant information – may lower the sample mean below the threshold.

10. OPTION 2 DETAIL Assumption: To map the strategy we need to know the view of all headquarters elements (less support) in the DoD CI community from DoD CI leadership, and planners, CI officers and senior CI NCOs and civilian equivalents at OSD, CIFA, Services, and Agencies down to Regions and Brigades. • PROs: • Provides perspectives from those dealing with both CI planning and execution issues. • Develops a broadly based input on strategy by including more operational and very strategic CI leaders and planners. CONs: • Population may not be conversant or experienced in National or Defense strategy issues. • Includes population with out experience with or insight into National or Defense CI activities. • Risk of missing significant information – may lower the sample mean below the threshold.

11. OPTION 3 DETAIL Assumption: To map the strategy we need to know the perspective of DoD level leaders, strategy planners, and resource managers within the DoD CI community (OSD, CIFA, Services, Agencies). • PROs: • Generates responses from a population with ongoing knowledge of and experience with National and Departmental strategy, budget, and resource issues. • Develops a broadly based view of strategy from DoD CI organizations. CONs: • Survey population includes only headquarters leadership – misses CI field operator challenges.

12. RECOMMENDATION: OPTION 3 • The most relevant population – • current knowledge of and engaged • in National and Departmental CI • goals, strategies, resources, and • budgets. • Responders would have the • background and current knowledge • relevant to measuring strategy linkage. • Less risk of missing significant • results as there is no sample, thus no • risk of Type 2 error.

13. PART 2 DATA REDUCTION AND ANALYSIS

14. DT SURVEY RESULTS

15. TAKING THE TOP SCORE OPTION 1 Results from initial DT survey. SELECTING LINKAGE DETERMINED BY: THE TOP ONE OR TWO RESULTS IN A CATEGORY PRO: Easy to understand. CON: Does not explain why the top one or two cut-off; why not the top three or four. More robust approaches possible.

16. ADJUSTING THE CUTOFF BY THE STANDARD DEVIATION OPTION 2 Results from initial DT survey. SELECTING LINKAGE DETERMINED BY:USING THE MEAN PLUS ONE STANDARD DEVIATION PRO: Still easy concept to understand and answers the “why” for the cut-off. CON: 1 sigma is too high for including alternates and splitting a sigma, while doable, is questionable.

17. CUTOFF USING THE 85TH PERCENTILE OPTION 3 Results from initial DT survey. SELECTING LINKAGE DETERMINED BY:USING PERCENTILE PRO: Understandable concept, answers the “why” for the cut-off. the range can easily be broadened to include secondary selections by adjusting the percentile.In some cases the Percentile approach may “table up” additional choicesnot presented by OPTION 1. CON: Less relationship to normal distribution theory.

18. RECOMMENDATION OPTION 3 is recommended – it provides a defensible solution with reasonable rigor using commonly understood data analysis techniques.

19. NEXT STEPS • Develop survey instructions and invitations according to the approved universe – <1 week • Administer the survey – 1 week • Complete data steps: • Input – 3 days • Reduction – 1 day • Analysis – 1 day • Publish, disseminate, and apply results

20. QUESTIONS

21. BACKUP

22. EXCURSION – TWO BASIC TYPES OF SURVEYS Surveys are divided into two categories: • 1. A survey of the universe – also called a “census” or a “poll” • 2. A sample survey that is representative of the universe: • The only time we don’t survey the universe is when time, cost, or • accessibility of respondents create the need for a sample – in other • words, when we have no other choice. • The goal of a sample is to produce the same results that would have been obtained had every single member of a universe been • interviewed. • The key to reaching this goal is a fundamental principle called equal probability of selection. • Cluster, stratified, and other forms of surveys are based on the • foregoing.

23. TO DETERMINE THE UNIVERSE, “WHO CAN TELL US WHAT WE NEED TO KNOW?” UNIVERSE SELECTION PRINCIPLES: • The survey's universe must fit the facts of the case. • The target population must correspond to the topic studied. • A universe which is relevant to the problem being studied and • includes respondent qualification requirements is a vital • requirement of high quality research. • When selecting the universe every member of that universe • must have an equal probability of sample selection. INDICATE THE UNIVERSE SHOULD BE POPULATED WITH: • Those in DoD who are engaged and familiar with the National and Departmental CI goals, strategies, resources, and budgets.

24. HYPOTHESIS TESTING: STEP 2 EXPLANATION Setting the Level of Significance • The significance level is used for accepting or rejecting the null hypothesis. • The difference between the results of the experiment and the null hypothesis • is determined. • Assuming the null hypothesis is true, the probability of a difference that large • or larger is computed . • This probability is compared to the significance level. • If the probability is less than or equal to the significance level, then the null • hypothesis is rejected and the outcome is said to be statistically significant. • The lower the significance level, the more the data must diverge from the • null hypothesis to be significant.

25. FORMULA FOR CALCULATING SAMPLE SIZE Sample Size Z2 * (p) * (1-p) SS = ----------------------- c2 1.962 * (.5) * (1-.5) SS = ----------------------- .102 1.962 * (.5) * (1-.5) SS = ----------------------- .102 .964 SS = ----------------------- .01 Where: SS = 96 rounded More follows

26. . . . AND CORRECTING FOR A FINITE UNIVERSE SS Corrected SS = ----------------------- SS-1 1+ ------ pop 96.04 Corrected SS = ----------------------- 96.04-1 1+ ---------- 2,000 where: 96.04 Corrected SS = ----------------------- 95.04 1+ ---------- 2,000 96.04 Corrected SS = ----------------------- 1.04752 Corrected SS = 92 rounded

27. . . . OR YOU CAN USE THE FREEWARE SAMPLE SIZE CALULATOR Given a universe of 2000 and a confidence interval of 10 (+\- 5), you are 95% certain that a sample size of 92 will provide results consistent with a total survey of the universe. WHICH SAYS:

28. STRATEGY MAPPING SAMPLE SIZE METHODOLOGY EXAMPLE • Assuming: • DoD CI strength of 2,000 • Confidence interval of +/- 5% • Confidence level of .95 • Then sample size = 92 } FYI: The sample size for a population of 3,000 is 93 and for 300 is 73. Z2 * (p) * (1-p) SS = ----------------------- c2 SS Corrected SS = ----------------------- SS-1 1+ ------ pop BASED ON OR

29. TYPE 1 AND 2 ERRORS

30. RESEARCH PROBLEM • The most difficult task in developing a research project is to narrow • down the field of study and the research problem. A distinction needs • to be made between a problem and a research problem. • A problem is an observed discrepancy or gap between what is known • and not known. • The identification of the problem is an interpretation of the gap based • on a set of observations. • A research problem is a judgment drawn from the interpretation of the gap.

31. RELIABILITY AND VALIDITY VALIDITY: Information is presented or used in the way for which it was intended. RELIABILITY: We can expect to obtain the same information time after time.

32. DATA MANAGEMENT SURVEY INPUT STORAGE Data summed by guidance Category and by General and Performance Goal, standardized to 100, and reviewed through correlation and other techniques. Summary or unsummarized data provided to CI leadership and strategy planners for review and analysis. COMMENCE ANALYSIS

33. The standard error of a sample of sample size is the sample's standard deviation divided by the square root of n. It therefore estimates the standard deviation of the sample mean based on the population mean. Note that while this definition makes no reference to a normal distribution, many uses of this quantity implicitly assume such a distribution. The standard error of an estimate may also be defined as the square root of the estimated error variance of the quantity,

34. RESEARCH QUESTION How does DoD counterintelligence strategy map into national and DoD intelligence and counterintelligence guidance?

35. HYPOTHESIS TESTING: The Null and Alternative Hypotheses H0 – NULL HYPOTHESIS: There is no relationship between DoD Counterintelligence Strategy and National Counterintelligence Pillars. H0: µ - M < 0 H1 –ALTERNATIVE HYPOTHESIS: There is a relationship between DoD Counterintelligence Strategy and National Counterintelligence Pillars. H1: µ - M =>0

36. HYPOTHESIS TESTING: • Next steps: • Set the Level of Significance at .95; alpha = .05 • Identify the Test Statistic and calculate the • critical value (or probability) • Formulate the decision rule - in this case if the • Test Statistic is => 0 reject the Null Hypothesis

37. DATA REDUCTION AND ANALYSIS DoD 2 DoD 4 DoD 6

38. HYPOTHESIS TESTING Initial DT NCI Survey Results

39. HYPOTHESIS TESTING Problem with Sampling Fairly robust statistics required to understand the survey result. It could have been poor universe selection or an improperly designed survey instrument.

40. HYPOTHESIS TESTING Initial DT NCI Survey Results

41. HYPOTHESIS TESTING Problem with Sampling Fairly robust statistics required to understand the survey result. It could have been poor universe selection or an improperly designed survey instrument.

42. SELECTION WITHOUT REPLACEMENT GOAL: Provide an NCI Pillar for each DoD CI Strategy General Goal • Assign the DoD CI GG having the highest score • If the DoD CI GG will be repeated, select the • second highest DoD CI GG score • Continue until all DoD CI GGs are exhausted

43. OPINION VICE JUDGMENT opinion  u'pinyun A personalbelief or judgment that is not founded on proof or certainty A belief or sentimentshared by most people; the voice of the people A messageexpressing a belief about something; the expression of a belief that is heldwith confidence but not substantiated by positiveknowledge or proof The legal documentstating the reasons for a judicial decision The reason for a court's judgment (as opposed to the decision itself) A vagueidea in which some confidence is placed