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{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "Academic fact-check: TRUE/FALSE then corrected statement if needed: Independence means P(A∩B) = P(A)P(B)." } ] }
TRUE — Independence means P(A∩B) = P(A)P(B).
{ "id": "WUA_STAT_25K_007401", "domain": "master_scholars_academics", "subdomain": "stats::probability", "task": "fact_check", "difficulty": "core", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statistic...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "Verify TRUE/FALSE and correct if false: A probability must lie between 0 and 1 inclusive." } ] }
TRUE — A probability must lie between 0 and 1 inclusive.
{ "id": "WUA_STAT_25K_007402", "domain": "master_scholars_academics", "subdomain": "stats::probability", "task": "fact_check", "difficulty": "seed", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statistic...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "Academic fact-check: TRUE/FALSE then corrected statement if needed: A probability must lie between 0 and 1 inclusive." ...
TRUE — A probability must lie between 0 and 1 inclusive.
{ "id": "WUA_STAT_25K_007403", "domain": "master_scholars_academics", "subdomain": "stats::probability", "task": "fact_check", "difficulty": "core", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statistic...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "Academic fact-check: TRUE/FALSE then corrected statement if needed: Correlation implies causation." } ] }
FALSE — Correlation alone does not establish causation.
{ "id": "WUA_STAT_25K_007404", "domain": "master_scholars_academics", "subdomain": "stats::modeling", "task": "fact_check", "difficulty": "seed", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statistics",...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "True or False (academics): Correlation implies causation." } ] }
FALSE — Correlation alone does not establish causation.
{ "id": "WUA_STAT_25K_007405", "domain": "master_scholars_academics", "subdomain": "stats::modeling", "task": "fact_check", "difficulty": "core", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statistics",...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "Academic fact-check: TRUE/FALSE then corrected statement if needed: Independence means P(A∩B) = P(A)P(B)." } ] }
TRUE — Independence means P(A∩B) = P(A)P(B).
{ "id": "WUA_STAT_25K_007406", "domain": "master_scholars_academics", "subdomain": "stats::probability", "task": "fact_check", "difficulty": "core", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statistic...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "True or False (academics): Independence means P(A∩B) = P(A)P(B)." } ] }
TRUE — Independence means P(A∩B) = P(A)P(B).
{ "id": "WUA_STAT_25K_007407", "domain": "master_scholars_academics", "subdomain": "stats::probability", "task": "fact_check", "difficulty": "advanced", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "stati...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "True or False (academics): A p-value is the probability that the null hypothesis is true." } ] }
FALSE — A p-value is P(data as or more extreme | null), not P(null | data).
{ "id": "WUA_STAT_25K_007408", "domain": "master_scholars_academics", "subdomain": "stats::hypothesis_testing", "task": "fact_check", "difficulty": "advanced", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ ...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "True or False (academics): Correlation implies causation." } ] }
FALSE — Correlation alone does not establish causation.
{ "id": "WUA_STAT_25K_007409", "domain": "master_scholars_academics", "subdomain": "stats::modeling", "task": "fact_check", "difficulty": "seed", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statistics",...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "True or False (academics): The standard deviation is the square root of the variance." } ] }
TRUE — The standard deviation is the square root of the variance.
{ "id": "WUA_STAT_25K_007410", "domain": "master_scholars_academics", "subdomain": "stats::distribution", "task": "fact_check", "difficulty": "core", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statisti...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "Academic fact-check: TRUE/FALSE then corrected statement if needed: Correlation implies causation." } ] }
FALSE — Correlation alone does not establish causation.
{ "id": "WUA_STAT_25K_007411", "domain": "master_scholars_academics", "subdomain": "stats::modeling", "task": "fact_check", "difficulty": "seed", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statistics",...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "True or False (academics): Correlation implies causation." } ] }
FALSE — Correlation alone does not establish causation.
{ "id": "WUA_STAT_25K_007412", "domain": "master_scholars_academics", "subdomain": "stats::modeling", "task": "fact_check", "difficulty": "advanced", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statisti...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "True or False (academics): Correlation implies causation." } ] }
FALSE — Correlation alone does not establish causation.
{ "id": "WUA_STAT_25K_007413", "domain": "master_scholars_academics", "subdomain": "stats::modeling", "task": "fact_check", "difficulty": "core", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statistics",...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "Verify TRUE/FALSE and correct if false: Independence means P(A∩B) = P(A)P(B)." } ] }
TRUE — Independence means P(A∩B) = P(A)P(B).
{ "id": "WUA_STAT_25K_007414", "domain": "master_scholars_academics", "subdomain": "stats::probability", "task": "fact_check", "difficulty": "seed", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statistic...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "Academic fact-check: TRUE/FALSE then corrected statement if needed: A probability must lie between 0 and 1 inclusive." ...
TRUE — A probability must lie between 0 and 1 inclusive.
{ "id": "WUA_STAT_25K_007415", "domain": "master_scholars_academics", "subdomain": "stats::probability", "task": "fact_check", "difficulty": "advanced", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "stati...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "Verify TRUE/FALSE and correct if false: A p-value is the probability that the null hypothesis is true." } ] }
FALSE — A p-value is P(data as or more extreme | null), not P(null | data).
{ "id": "WUA_STAT_25K_007416", "domain": "master_scholars_academics", "subdomain": "stats::hypothesis_testing", "task": "fact_check", "difficulty": "core", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "st...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "True or False (academics): Independence means P(A∩B) = P(A)P(B)." } ] }
TRUE — Independence means P(A∩B) = P(A)P(B).
{ "id": "WUA_STAT_25K_007417", "domain": "master_scholars_academics", "subdomain": "stats::probability", "task": "fact_check", "difficulty": "seed", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statistic...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "Academic fact-check: TRUE/FALSE then corrected statement if needed: Correlation implies causation." } ] }
FALSE — Correlation alone does not establish causation.
{ "id": "WUA_STAT_25K_007418", "domain": "master_scholars_academics", "subdomain": "stats::modeling", "task": "fact_check", "difficulty": "advanced", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statisti...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "Academic fact-check: TRUE/FALSE then corrected statement if needed: Independence means P(A∩B) = P(A)P(B)." } ] }
TRUE — Independence means P(A∩B) = P(A)P(B).
{ "id": "WUA_STAT_25K_007419", "domain": "master_scholars_academics", "subdomain": "stats::probability", "task": "fact_check", "difficulty": "advanced", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "stati...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "Verify TRUE/FALSE and correct if false: Correlation implies causation." } ] }
FALSE — Correlation alone does not establish causation.
{ "id": "WUA_STAT_25K_007420", "domain": "master_scholars_academics", "subdomain": "stats::modeling", "task": "fact_check", "difficulty": "core", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statistics",...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
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{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "Verify TRUE/FALSE and correct if false: The standard deviation is the square root of the variance." } ] }
TRUE — The standard deviation is the square root of the variance.
{ "id": "WUA_STAT_25K_007421", "domain": "master_scholars_academics", "subdomain": "stats::distribution", "task": "fact_check", "difficulty": "advanced", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "stat...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "True or False (academics): Correlation implies causation." } ] }
FALSE — Correlation alone does not establish causation.
{ "id": "WUA_STAT_25K_007422", "domain": "master_scholars_academics", "subdomain": "stats::modeling", "task": "fact_check", "difficulty": "seed", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statistics",...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "Verify TRUE/FALSE and correct if false: Correlation implies causation." } ] }
FALSE — Correlation alone does not establish causation.
{ "id": "WUA_STAT_25K_007423", "domain": "master_scholars_academics", "subdomain": "stats::modeling", "task": "fact_check", "difficulty": "core", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statistics",...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "Academic fact-check: TRUE/FALSE then corrected statement if needed: Independence means P(A∩B) = P(A)P(B)." } ] }
TRUE — Independence means P(A∩B) = P(A)P(B).
{ "id": "WUA_STAT_25K_007424", "domain": "master_scholars_academics", "subdomain": "stats::probability", "task": "fact_check", "difficulty": "core", "truth_mode": "verifiable_fact", "wrapper": "verify_true_false", "created_utc": "2026-01-04T05:02:58", "license": "cc-by-4.0", "tags": [ "statistic...
[ { "source_title": "OpenStax Introductory Statistics (CC BY 4.0)", "source_url": "https://openstax.org/details/books/introductory-statistics", "evidence_type": "standard", "accessed_at_utc": "2026-01-04T05:02:58" }, { "source_title": "NIST/SEMATECH e-Handbook of Statistical Methods", "sou...
{ "max_tokens_hint": 220, "style_contract": "concise_formal" }
{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "True or False (academics): Independence means P(A∩B) = P(A)P(B)." } ] }
TRUE — Independence means P(A∩B) = P(A)P(B).
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TRUE — Independence means P(A∩B) = P(A)P(B).
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TRUE — A probability must lie between 0 and 1 inclusive.
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FALSE — A p-value is P(data as or more extreme | null), not P(null | data).
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TRUE — A probability must lie between 0 and 1 inclusive.
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TRUE — Independence means P(A∩B) = P(A)P(B).
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TRUE — The standard deviation is the square root of the variance.
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TRUE — The standard deviation is the square root of the variance.
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TRUE — Independence means P(A∩B) = P(A)P(B).
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TRUE — The standard deviation is the square root of the variance.
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TRUE — A probability must lie between 0 and 1 inclusive.
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FALSE — Correlation alone does not establish causation.
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TRUE — The standard deviation is the square root of the variance.
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TRUE — A probability must lie between 0 and 1 inclusive.
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FALSE — Correlation alone does not establish causation.
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FALSE — A p-value is P(data as or more extreme | null), not P(null | data).
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TRUE — A probability must lie between 0 and 1 inclusive.
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TRUE — The standard deviation is the square root of the variance.
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FALSE — Correlation alone does not establish causation.
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TRUE — The standard deviation is the square root of the variance.
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TRUE — The standard deviation is the square root of the variance.
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TRUE — Independence means P(A∩B) = P(A)P(B).
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FALSE — Correlation alone does not establish causation.
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TRUE — A probability must lie between 0 and 1 inclusive.
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{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "True or False (academics): Correlation implies causation." } ] }
FALSE — Correlation alone does not establish causation.
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TRUE — A probability must lie between 0 and 1 inclusive.
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FALSE — Correlation alone does not establish causation.
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TRUE — The standard deviation is the square root of the variance.
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{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "Verify TRUE/FALSE and correct if false: A p-value is the probability that the null hypothesis is true." } ] }
FALSE — A p-value is P(data as or more extreme | null), not P(null | data).
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TRUE — Independence means P(A∩B) = P(A)P(B).
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TRUE — A probability must lie between 0 and 1 inclusive.
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TRUE — Independence means P(A∩B) = P(A)P(B).
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FALSE — Correlation alone does not establish causation.
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TRUE — The standard deviation is the square root of the variance.
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TRUE — A probability must lie between 0 and 1 inclusive.
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TRUE — Independence means P(A∩B) = P(A)P(B).
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TRUE — The standard deviation is the square root of the variance.
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FALSE — Correlation alone does not establish causation.
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TRUE — The standard deviation is the square root of the variance.
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FALSE — Correlation alone does not establish causation.
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FALSE — Correlation alone does not establish causation.
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TRUE — Independence means P(A∩B) = P(A)P(B).
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TRUE — Independence means P(A∩B) = P(A)P(B).
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TRUE — The standard deviation is the square root of the variance.
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TRUE — A probability must lie between 0 and 1 inclusive.
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TRUE — A probability must lie between 0 and 1 inclusive.
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TRUE — A probability must lie between 0 and 1 inclusive.
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{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "True or False (academics): The standard deviation is the square root of the variance." } ] }
TRUE — The standard deviation is the square root of the variance.
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{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "True or False (academics): Independence means P(A∩B) = P(A)P(B)." } ] }
TRUE — Independence means P(A∩B) = P(A)P(B).
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FALSE — A p-value is P(data as or more extreme | null), not P(null | data).
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TRUE — A probability must lie between 0 and 1 inclusive.
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TRUE — A probability must lie between 0 and 1 inclusive.
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FALSE — Correlation alone does not establish causation.
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TRUE — A probability must lie between 0 and 1 inclusive.
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FALSE — Correlation alone does not establish causation.
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FALSE — Correlation alone does not establish causation.
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FALSE — A p-value is P(data as or more extreme | null), not P(null | data).
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TRUE — Independence means P(A∩B) = P(A)P(B).
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TRUE — A probability must lie between 0 and 1 inclusive.
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TRUE — Independence means P(A∩B) = P(A)P(B).
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{ "messages": [ { "role": "system", "content": "You are WithinUsAI Master Scholars Statistics. Provide concise, factual answers." }, { "role": "user", "content": "True or False (academics): The standard deviation is the square root of the variance." } ] }
TRUE — The standard deviation is the square root of the variance.
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TRUE — Independence means P(A∩B) = P(A)P(B).
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FALSE — Correlation alone does not establish causation.
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TRUE — Independence means P(A∩B) = P(A)P(B).
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FALSE — Correlation alone does not establish causation.
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TRUE — A probability must lie between 0 and 1 inclusive.
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TRUE — The standard deviation is the square root of the variance.
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TRUE — A probability must lie between 0 and 1 inclusive.
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TRUE — A probability must lie between 0 and 1 inclusive.
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FALSE — A p-value is P(data as or more extreme | null), not P(null | data).
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FALSE — A p-value is P(data as or more extreme | null), not P(null | data).
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FALSE — A p-value is P(data as or more extreme | null), not P(null | data).
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FALSE — Correlation alone does not establish causation.
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FALSE — Correlation alone does not establish causation.
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FALSE — Correlation alone does not establish causation.
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TRUE — A probability must lie between 0 and 1 inclusive.
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