Based on our class discussion and materials, an entrepreneur: (select all that apply)

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Question restatement: Based on our class discussion and materials, an entrepreneur (select all that apply) – with two options provided for evaluation.
Option 1: 'should develop falsifiable hypotheses with success thresholds in tests' This aligns with standard entrepreneurial and scientific thinking: hypotheses should be falsifiable so they can be tested, and having predefined success thresholds helps determine when a hypothesis is supported or refuted by data. The emphasis on falsifiability also prevents vague or untestable claims, which is consistent with rigorous experimentation in entrepreneurship.
Option 2: 'is at risk of confirming a hypothesis that is not true (a false positive) by having the wrong test group' This statement highlights a real risk in experimentation: if the test group is not appropriate or is biased, one may observe results that appear to support a hypothesis even though it is false. This is a caution about experimental design and sampling – a false positive occurs when you incorrectly conclude that a hypothesis is true due to flawed methodology rather than true effect.
Now, evaluating each option in more depth:
- For option 1, the rationale is that debuggable, testable hypotheses with explicit success criteria enable learning loops and empirical validation, which are central to many entrepreneurial processes like lean startup methods. The idea is to frame experiments in a way that outcomes clearly confirm or disconfirm, guiding next steps rather than relying on intuition alone.
- For option 2, the concern about false positives underscores the importance of correct experimental setup: the test group must be representative, controls may be needed, and sample size should be adequate to avoid spurious conclusions. If the wrong cohort or biased grouping is used, the data may falsely indicate that a hypothesis holds, which can mislead strategy and product decisions.
Potential misconceptions to watch for:
- If someone thinks hypotheses cannot be falsified, they would reject the core principle of scientific testing; that view would undermine iterative learning.
- If someone assumes any significant result in testing proves the hypothesis, they overlook the possibility of statistical artifacts, biases, or p-hacking that can produce false positives.
- If one assumes test groups are interchangeable or that test conditions perfectly mirror reality, they may underestimate external validity concerns and overestimate the strength of evidence.
In sum, both statements reflect important and complementary aspects of entrepreneurial testing: construct hypotheses that are testable and define thresholds (option 1), while remaining vigilant about experimental design to avoid false positives from an inappropriate test group (option 2).

ES 212 003 FA 2025 Quiz 2

Based on our class discussion and materials, an entrepreneur: (select all that apply)

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