{"uid":"cap_QwZRJ6WhLUM0QlFExePzM","slug":"kihustle-spearman-correlation-api-d87a103e","name":"KiHustle Spearman Correlation 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/json-correlation-spearman?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"series_a":{"type":"array","items":{"type":"number"}},"series_b":{"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_kU0PG7qBBsBVM_JgJn2vJ","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":"Computes the Spearman rank correlation coefficient between two numeric series.","exampleAgentPrompt":"Can you compute the Spearman rank correlation between these two series: series A is [10, 20, 30, 40, 50] and series B is [12, 18, 33, 37, 55]?","exampleUseCases":[{"title":"Marketing channel rank correlation","prompt":"I have two lists of numbers — one is the ranking of our ad channels by spend and the other is by conversions. Can you run a Spearman correlation on series_a [1,2,3,4,5] and series_b [2,1,4,3,5] to see how aligned they are?"},{"title":"Student test score monotonic relationship","prompt":"I have two sets of student scores from two different exams — series_a is [55,72,63,88,91] and series_b is [60,70,65,85,95]. Please calculate the Spearman rank correlation to see if performance on one exam predicts the other."},{"title":"Financial indicator rank association","prompt":"Can you run a Spearman correlation between these two financial time-series arrays — series_a [100,200,150,300,250] and series_b [110,210,140,310,260] — to check if they move together in rank order?"}],"resultDescription":"Returns a JSON object with a 'result' field containing the computed Spearman correlation value and a 'status' field indicating success or failure of the computation.","failureModes":["Mismatched series lengths may cause an error or undefined result","Empty arrays passed as input may return an error","Non-numeric values in either series may cause processing failure","Identical values in a series (ties) may produce unexpected rho values","Malformed JSON body returns a 4xx error"],"whenToPreferThis":"Use this endpoint when you need a non-parametric, rank-based measure of monotonic association between two numeric sequences, especially when data may not be normally distributed or contains outliers. Prefer Spearman over Pearson when the relationship between variables is monotonic but not necessarily linear.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-13T12:46:59.316Z","isFirstParty":false,"canonicalSlug":"kihustle-spearman-correlation-api-d87a103e"}