{"uid":"cap_fAdQSzXSvVB59UBSoHjdu","slug":"kihustle-spearman-rank-correlation-api-12c6bd25","name":"KiHustle Spearman Rank 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/agents/api/v1/json-correlation-spearman","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_o8SS7aeTIG_1rNOXn-3GZ","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 numerical data series","exampleAgentPrompt":"Can you compute the Spearman rank correlation between these two series — series A is [1, 2, 3, 4, 5] and series B is [5, 6, 7, 8, 7]?","exampleUseCases":[{"title":"Survey data monotonic relationship check","prompt":"I have two sets of survey scores — respondents' age ranks and their satisfaction scores — can you calculate the Spearman correlation to see if older respondents tend to be more satisfied? Series A is [23,45,31,52,60,28,47] and series B is [3,7,4,8,9,4,6]."},{"title":"Financial variable rank association","prompt":"I want to know the Spearman rank correlation between these two financial time series to see if they move together non-parametrically — series A is [102,98,110,115,108] and series B is [50,48,55,60,53]."},{"title":"Academic performance correlation analysis","prompt":"Can you check whether students' study hours and their exam scores have a monotonic relationship using Spearman correlation? Hours are [1,2,3,5,8,10] and scores are [40,45,55,65,80,90]."}],"resultDescription":"Returns a JSON object containing the Spearman rank correlation coefficient (rho) between the two input series, along with a status field indicating success. The result scalar ranges from -1 (perfect inverse rank correlation) to +1 (perfect rank correlation), with 0 indicating no monotonic relationship.","failureModes":["Mismatched array lengths between series_a and series_b — may return an error or undefined result","Empty arrays provided — likely returns an error response","Non-numeric values in arrays — schema validation may reject input","Arrays with too few elements for meaningful correlation — result may be unreliable","Network or payment failure returns 402 if USDC payment not processed"],"whenToPreferThis":"Choose this endpoint when you need a non-parametric measure of association between two numeric series that does not assume a normal distribution. Prefer Spearman over Pearson when data may be ordinal, contain outliers, or have a monotonic but non-linear relationship. Ideal for ranked survey data, financial ranks, or any scenario where rank order matters more than exact values.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T07:06:37.087Z","isFirstParty":false}