{"doi":"10.1002/9781118445112.stat05936","title":"Power, Sensitivity and Alignment","abstract":"<jats:title>Abstract</jats:title>\n          <jats:p>In the Neyman–Pearson approach to the theory of hypothesis testing, power is the probability of rejecting the null hypothesis when an alternative hypothesis is true.</jats:p>\n          <jats:p>It therefore depends on the specific alternative, and may lead to the selection of a test statistic that provides satisfactory power. In particular, one might choose a uniformly most powerful unbiased test (unbiasedness here indicating minimum power at the null hypothesis). Power considerations are often used in the determination of sample size.</jats:p>","journal":"Wiley StatsRef: Statistics Reference Online","year":2014,"id":21834,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":139150,"name":"K. E. Muller","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"24259432","pmcid":null,"openalex_id":"https://openalex.org/W1530986061","authors":[],"funders":[],"total_grants":0,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[],"oa_status":"closed","license":"http://doi.wiley.com/10.1002/tdm_license_1.1","oa_locations":[{"url":"https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781118445112.stat05936","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/full-xml/10.1002/9781118445112.stat05936","host_type":"publisher"},{"url":"https://doi.org/10.1002/9781118445112.stat05936","host_type":"journal"}],"fields_of_study":["Advanced Statistical Methods and Models","Mathematics"],"mesh_terms":[],"keywords":["Null hypothesis","Alternative hypothesis","Null (SQL)","Statistical power","Sample size determination","Statistics","Test statistic","Statistical hypothesis testing","Statistic","Mathematics","Power (physics)","Selection (genetic algorithm)","Econometrics","Sample (material)","Sensitivity (control systems)","Computer science","Artificial intelligence","Data mining","Engineering"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Reduced inequalities"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-06-06T16:56:05.245580Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}