{"uid":"cap_kcPU_kOjX4OaVizgY6Dsa","slug":"cohen-s-d-effect-size-calculator-9c3ea74b","name":"Cohen's d Effect Size Calculator","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/effect-size-cohens-d","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"group_a":{"type":"array","items":{"type":"number"}},"group_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_wbVonmKAX8XvSEXFt-Bsu","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 Cohen's d effect size statistic between two numeric groups to quantify the magnitude of difference between them","exampleAgentPrompt":"Calculate Cohen's d effect size between these two groups for me — group A is [2.3, 3.1, 2.8, 3.5, 2.9] and group B is [4.1, 4.8, 3.9, 5.2, 4.5].","exampleUseCases":[{"title":"A/B test effect size analysis","prompt":"I ran an A/B test and want to know the effect size. Control group scores are [55, 60, 58, 62, 57] and treatment group scores are [68, 72, 65, 70, 74]. Can you compute Cohen's d to tell me how meaningful the difference is?"},{"title":"Clinical trial group comparison","prompt":"I have pre-treatment pain scores [7, 8, 6, 9, 7, 8] and post-treatment scores [3, 4, 2, 5, 3, 4]. Calculate Cohen's d so I can report the effect size of the intervention."},{"title":"Educational intervention evaluation","prompt":"My students who received tutoring scored [85, 88, 90, 82, 87] on the final exam, and those who didn't scored [72, 75, 70, 78, 74]. What's Cohen's d to quantify how effective the tutoring was?"}],"resultDescription":"Returns a JSON object with a computed result value (Cohen's d statistic) and a success status indicator. Cohen's d represents the standardized mean difference between the two groups, where 0.2 is considered small, 0.5 medium, and 0.8+ large effect.","failureModes":["Empty arrays for group_a or group_b may cause computation errors","Arrays with a single element may produce unreliable standard deviation estimates","Non-numeric values in arrays will likely cause processing failures","Extremely large arrays may increase latency","Missing required fields returns an error status"],"whenToPreferThis":"Choose this endpoint when you need a quick, cheap ($0.002) statistical computation of Cohen's d effect size between two groups without setting up a local statistics library. Ideal for agents automating research reporting, A/B test summarization, or educational assessment pipelines where effect size must be calculated programmatically at scale.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T00:57:40.726Z","isFirstParty":false}