{"id":"W1525379006","doi":"10.18438/b8fw2h","title":"A Statistical Primer: Understanding Descriptive and Inferential Statistics","year":2007,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Statistics Education and Methodologies","field":"Mathematics","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Descriptive statistics; Statistical inference; Statistics; Computer science; Statistical analysis; Statistical hypothesis testing; Variance (accounting); Analysis of variance; Data science; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001438101,0.0001419439,0.0001590173,0.0001883977,0.0001992517,0.0003462833,0.0000767079,0.00007876928,0.0003055544],"category_scores_gemma":[0.0191068,0.0001317226,0.00001201644,0.0001794002,0.0001762321,0.03666637,0.00007124092,0.000220217,0.00001422917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003186585,"about_ca_system_score_gemma":0.000211908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005224395,"about_ca_topic_score_gemma":1.744621e-7,"domain_scores_codex":[0.9986434,0.0002836677,0.0004761638,0.0001383962,0.0002472631,0.0002111316],"domain_scores_gemma":[0.9768353,0.02246515,0.0003217679,0.0001395142,0.00007482413,0.0001634329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003266821,0.00002867451,0.0003866014,0.000153538,0.00001670514,0.00000425595,0.0007106803,9.272719e-7,0.00001399453,0.9798612,0.01086528,0.007631473],"study_design_scores_gemma":[0.001904076,0.0007574406,0.02731948,0.000611792,0.0004326362,0.0001676974,0.03424908,0.004503899,0.002694849,0.5862367,0.3401629,0.000959484],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009416856,0.000116756,0.9908429,0.004575033,0.0003069516,0.0002440612,0.0001278444,0.0001033231,0.002741411],"genre_scores_gemma":[0.063538,0.0006476639,0.926821,0.00869417,0.0000604743,0.000009770749,0.00008212964,0.00001267515,0.0001341176],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3936245,"threshold_uncertainty_score":0.9891557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1889159892326802,"score_gpt":0.4036950962914831,"score_spread":0.2147791070588029,"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."}}