Quantitative methods
Choose the right calculation and make its assumptions visible in the deliverable.
Descriptive analysis
Frequencies, distributions, means, medians and crosstabs describe the analyzed sample. Declare scale ranges, top/bottom-box thresholds, recodes and nets explicitly. Do not infer the intended scale from the values people happened to choose.
Every exported table should retain its base, denominator, missingness and weight status. Compare the same definitions across segments and waves.
Weights and inference
Weighting needs a stated target population and supported target categories. Review convergence, extreme weights and effective sample size before using the result. Weighting an opt-in sample does not establish probability representativeness.
Statistical comparisons depend on the sampling design, group overlap, repeated responses, weights and base size. Read the method disclosure. A suppressed significance result is not evidence of no difference.
Separate description from inference Use descriptive comparisons when the assumptions for a statistical test are not established. Complex survey inference requires the appropriate configured survey method; do not apply an unweighted independent-sample test to weighted or repeated data.
Specialized studies
| Method | Review before interpreting |
|---|---|
| Concept tests | Exposure, allocation, question wording and base for each concept. |
| MaxDiff | Item/task design, respondent-level dependence and estimator diagnostics. |
| Van Westendorp | Four ordered price perceptions, currency/unit and curve limitations. |
| Gabor-Granger | The configured price ladder, purchase-intent rule and valid respondent base. |
| Tracking waves | Question identity, eligibility, source mix and comparability over time. |
Configure the task in Design and use the method disclosed by the saved analysis. A model-generated recommendation is not a substitute for a measured answer or a verified estimator.