Framing Opportunities for Effective Data Analysis - PDF
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This document presents multiple-choice questions related to data-driven decision making. It covers topics such as question framing, validating assumptions, and narrowing down problems effectively, emphasizing the importance of data in analysis for effective decision-making.
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**Question 1: Multiple Choice** **Which steps should you take to ensure your decision making is data driven?** - **Options:** 1. Stick with whatever solution emerges first and see it through. 2. Collect any available information on the problem. 3. Determine exactly what the act...
**Question 1: Multiple Choice** **Which steps should you take to ensure your decision making is data driven?** - **Options:** 1. Stick with whatever solution emerges first and see it through. 2. Collect any available information on the problem. 3. Determine exactly what the actual problem is. 4. Propose a general explanation for the problem. 5. Do tests to check whether the supposed explanation is correct. 6. Interpret results in a way that ensures they support the initial hypothesis. - **Correct Answers:** 2, 3, 4, 5. **Question 2: Multiple Choice** **Which questions should you ask when attempting to narrow down a problem?** - **Options:** 1. Who caused the problem or the situation? 2. Who does the problem affect? 3. When does the decision need to be made? 4. Why does the issue matter? 5. What decision needs to be made? 6. What similar problems have been addressed? 7. What exactly is the problem? - **Correct Answers:** 2, 3, 4, 5, 7. **Question 3: Multiple Choice** **Which steps should be taken when attempting to test and validate assumptions?** - **Options:** 1. Assess whether assumptions are based on value-adding information. 2. Evaluate the assumptions by asking questions about their nature and basis. 3. Document and describe the rationale for the assumptions being made. 4. Determine whether assumptions are shared by similar organizations within the sector. 5. Solicit views and opinions of external experts on the validity of the assumptions. - **Correct Answers:** 1, 2, 3. **Question 4: Multiple Choice** **Which steps would help create an initial problem statement?** - **Options:** 1. Extract the information needed to answer the questions in the problem statement. 2. Determine which questions need to be asked in order to complete the problem statement. 3. Gather the information needed to answer the fundamental questions in the problem statement. 4. Initiate discussion with all involved stakeholders about the nature and details of the problem. 5. Specify questions that will result in a meaningful problem statement. 6. Complete the problem statement template and then assess its sufficiency. - **Correct Answers:** 1, 2, 3, 4. **Question 5: Multiple Choice** **Which activities are key to refining and finalizing problem statements?** - **Options:** 1. Check for gaps and ambiguities, ensuring there\'s enough data to proceed with confidence. 2. Complete the problem statement template, ensuring there are no gaps or ambiguities. 3. Identify the fundamental questions that need to be asked in order to complete the statement. 4. Ensure questions are specific and relevant to the problem so the resulting statement is meaningful. - **Correct Answers:** 2, 4. **What is the first step in ensuring decision making is data-driven?** - **Options:** 1. Collecting relevant data. 2. Formulating a hypothesis. 3. Identifying and defining the problem. 4. Interpreting the results of tests. - **Correct Answer:** 3. Identifying and defining the problem. **Question 7: Multiple Choice** **Which of the following is a critical aspect of narrowing down a problem effectively?** - **Options:** 1. Selectively listening to information that supports existing biases. 2. Making assumptions without verifying them. 3. Clarifying what the problem specifically entails. 4. Ignoring details that may lead to uncovering new issues. - **Correct Answer:** 3. Clarifying what the problem specifically entails. **Question 8: Multiple Choice** **What should be done after formulating a hypothesis in a data-driven decision process?** - **Options:** 1. Test the hypothesis through experiments. 2. Accept the hypothesis as correct without testing. 3. Immediately implement changes based on the hypothesis. 4. Disseminate the hypothesis to stakeholders as a final conclusion. - **Correct Answer:** 1. Test the hypothesis through experiments. **Question 9: Multiple Choice** **When refining and finalizing problem statements, what is important to ensure about the questions being asked?** - **Options:** 1. They should be broad and general. 2. They should lead to actionable insights. 3. They should confirm pre-existing beliefs. 4. They should be posed to as few stakeholders as possible. - **Correct Answer:** 2. They should lead to actionable insights. **Question 10: Multiple Choice** **Which of the following is a key component of a well-defined problem statement?** - **Options:** 1. Vague descriptions of the problem\'s context. 2. Assumptions that are not validated with data. 3. Clear identification of who is affected by the problem. 4. Limited data to support the scope of the problem. - **Correct Answer:** 3. Clear identification of who is affected by the problem.