{"id":"W3215800506","doi":"10.13052/jrss0974-8024.14210","title":"Estimation of Finite Population Variance Under Stratified Sampling Technique","year":2021,"lang":"en","type":"article","venue":"Journal of Reliability and Statistical Studies","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Estimator; Stratified sampling; Statistics; Sampling (signal processing); Population; Mathematics; Population variance; Sampling design; Simple random sample; Variance (accounting); Mean squared error; Sample (material); Sample size determination; Survey sampling; Cluster sampling; Ratio estimator; Econometrics; Bias of an estimator; Minimum-variance unbiased estimator; Computer science; Demography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01070166,0.000725928,0.001381652,0.001343633,0.0004020358,0.0009380133,0.001312081,0.0008173449,0.001604124],"category_scores_gemma":[0.03481828,0.0003510778,0.001292074,0.001490849,0.0008288362,0.001196471,0.0009660416,0.0007179333,0.0003978907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007661175,"about_ca_system_score_gemma":0.001751036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003321231,"about_ca_topic_score_gemma":0.002109461,"domain_scores_codex":[0.9884878,0.008445316,0.000367792,0.0009387376,0.001495983,0.0002644217],"domain_scores_gemma":[0.9901743,0.00628357,0.0009259806,0.001109561,0.001428327,0.00007823641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004887317,0.0001829911,0.0521961,0.001235531,0.0009569101,0.0007380592,0.001333851,0.1838643,0.01013273,0.3201146,0.005009069,0.4237472],"study_design_scores_gemma":[0.0001622953,0.0006415488,0.01713427,0.0003792753,0.0005112157,0.0007584171,0.0003337387,0.8079476,0.01029448,0.1499831,0.01173338,0.0001206604],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006573813,0.0001935415,0.9924222,0.00004331653,0.0000310641,0.0001441912,0.00006841807,0.0001017869,0.000421728],"genre_scores_gemma":[0.3072917,0.001029269,0.6888175,0.0001267686,0.00009146344,0.0009870608,0.0004834989,0.00004114466,0.001131676],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01070166,"threshold_uncertainty_score":0.05659646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.154129987016927,"score_gpt":0.4240133910827824,"score_spread":0.2698834040658554,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}