Which component of Analytic Design best matches the concept: Generate plausible alternatives to the analytic conclusions. Alternative hypotheses should be identified.

Which component of Analytic Design best matches the concept: Generate plausible alternatives to the analytic conclusions. Alternative hypotheses should be identified.

• A. Assess/evaluate analytic finding
• B. Confidence selection
• C. Analysis of alternatives
• D. Impact of remaining gaps and assumptions

Answer: (C)

The main idea here is to consider alternative explanations and hypotheses to test how solid a conclusion is. That approach—asking, “What else could explain these findings, and what would distinguish those possibilities?”—is what Analysis of alternatives is all about. It involves generating plausible alternative explanations to the analytic conclusion, laying out alternative hypotheses, and identifying what evidence would help discriminate among them. This keeps the analysis from fixing on a single narrative and helps reveal what data or tests are needed to adjudicate between competing explanations, increasing the robustness of the final assessment. Other components focus on different parts of the process. Assessing or evaluating the analytic finding centers on judging its quality, limitations, and strength given the current evidence. Confidence selection deals with how confident we are in the conclusion based on the available data. The impact of remaining gaps and assumptions examines how unanswered questions or assumptions might affect the conclusion. None of these explicitly require generating and weighing alternative explanations in the way Analysis of alternatives does.

The main idea here is to consider alternative explanations and hypotheses to test how solid a conclusion is. That approach—asking, “What else could explain these findings, and what would distinguish those possibilities?”—is what Analysis of alternatives is all about. It involves generating plausible alternative explanations to the analytic conclusion, laying out alternative hypotheses, and identifying what evidence would help discriminate among them. This keeps the analysis from fixing on a single narrative and helps reveal what data or tests are needed to adjudicate between competing explanations, increasing the robustness of the final assessment.

Other components focus on different parts of the process. Assessing or evaluating the analytic finding centers on judging its quality, limitations, and strength given the current evidence. Confidence selection deals with how confident we are in the conclusion based on the available data. The impact of remaining gaps and assumptions examines how unanswered questions or assumptions might affect the conclusion. None of these explicitly require generating and weighing alternative explanations in the way Analysis of alternatives does.