{"uid":"cap_hybYFqSLw-LPvY50uUjCQ","slug":"kihustle-paired-t-test-api-a789fd8e","name":"KiHustle Paired T-Test API","description":"Kostenlose Guides, Solo-Playbooks und Artikel zu KI, Automation und Side Hustles — für Menschen, die mit echten Systemen online Einkommen aufbauen wollen. Transparent finanziert über faire Affiliate-Links.","url":"https://kihustle.tech/nexus/api/v1/t-test-paired","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"after":{"type":"array","items":{"type":"number"}},"before":{"type":"array","items":{"type":"number"}}}},"responseSchema":{"type":"json","example":{"result":"processed","status":"success"}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.002","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.002/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_gtPiyMxW36sa9Bdf5tnHz","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.002","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Performs a paired (dependent samples) t-test on two matched numeric arrays to determine statistical significance of the difference between them","exampleAgentPrompt":"Run a paired t-test on my before and after measurements — before: [12.3, 15.1, 9.8, 11.5, 14.2] and after: [14.1, 16.8, 11.2, 13.0, 15.9] — and tell me if the difference is statistically significant.","exampleUseCases":[{"title":"Pre/post intervention significance check","prompt":"I ran an experiment with 6 participants and measured their scores before and after a training session. Before: [72, 68, 75, 80, 65, 70], after: [78, 74, 80, 85, 71, 76]. Run a paired t-test and tell me if the improvement is statistically significant."},{"title":"A/B testing matched pairs analysis","prompt":"I have conversion rates for the same 8 users under two different UI designs — old design: [0.12, 0.18, 0.09, 0.22, 0.15, 0.11, 0.20, 0.17] and new design: [0.15, 0.21, 0.13, 0.25, 0.18, 0.14, 0.23, 0.19]. Do a paired t-test to see if the new design actually improves conversions."},{"title":"Medical treatment effect evaluation","prompt":"These are blood pressure readings for 5 patients before and after a medication — before: [145, 138, 152, 160, 142], after: [132, 128, 140, 149, 135]. Compute a paired t-test so I can report whether the treatment had a statistically significant effect."}],"resultDescription":"Returns a JSON object with a 'result' field indicating the computed outcome and a 'status' field confirming success. In practice for a paired t-test this should include the t-statistic, degrees of freedom, and p-value indicating whether the difference between before and after arrays is statistically significant.","failureModes":["Mismatched array lengths (before and after arrays must have equal number of elements)","Empty or null arrays causing computation failure","Non-numeric values in input arrays","Arrays with fewer than 2 elements (insufficient degrees of freedom)","Generic 'processed'/'success' response may lack granular statistical details like p-value or confidence intervals"],"whenToPreferThis":"Choose this endpoint when you have paired/matched samples (same subjects measured twice, e.g. before and after an intervention) and need to test whether the mean difference is statistically significant. Prefer over independent t-test endpoints when observations are naturally paired. Useful in scientific experiments, A/B tests with matched users, or any repeated-measures scenario.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T00:57:33.509Z","isFirstParty":false}