Every experiment should list the success metric (i.e., success criteria) for your experiment metric. Given the success metrics listed below, select the best success metric (or criteria).

Question

BlackTom AI · Accepted Answer

Start by identifying what the question is asking: choose the best success metric (success criterion) from the given options.
Option 1: 'The hypothesis is supported if everyone likes it.' This is imprecise and unrealistic as a metric. 'Everyone' liking it is rarely measurable, highly unlikely, and does not translate into a clear, testable threshold or data collection method. It also leaves ambiguity about what 'like' means and how to quantify it.
Option 2: 'The hypothesis is supported if feedback is positive.' While positive feedback is informative, it is vague unless you specify what constitutes 'positive' and how it will be measured (e.g., a rating scale, sentiment analysis, or a minimum percentage expressing satisfaction). Without concrete thresholds, this fails to provide a testable success criterion for an experiment.
Option 3: 'The hypothesis is supported if 5% of website visitors add an item to their shopping cart.' This provides a concrete, measurable threshold (5%), a clear behavior to track (adding an item to cart), and a defined population (website visitors). It aligns with best practices for success criteria by turning the hypothesis into a specific, verifiable metric that can be observed and analyzed statistically.
Option 4: 'The hypothesis is supported if it sells.' Selling is a broad outcome that depends on many factors beyond the experiment's direct effect or scope. It also lacks a defined threshold (e.g., units sold, revenue, conversion rate) and may conflate long-term business success with a single experiment, reducing the precision of the metric.
In summary, the strongest, most actionable criterion is the one that translates the hypothesis into a specific, measured behavior with a quantifiable threshold, which is captured by Option 3. The other options lack concrete definitions, thresholds, or testability necessary for a reliable experimental success criterion.

MGT_2064_17971_202501 Final Exam

Every experiment should list the success metric (i.e., success criteria) for your experiment metric. Given the success metrics listed below, select the best success metric (or criteria).

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