{"doi":"10.1002/9781119109075.ch5","title":"Sampling from populations","abstract":null,"journal":"Essential Statistics for the Pharmaceutical Sciences","year":2015,"id":667741,"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":[],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Sampling from populations","abstract":"This chapter distinguishes between samples and populations and it describes the way in which sample size and the standard deviation (SD) jointly influence random sampling error. It shows how the Standard Error of the Mean (SEM) can be used to indicate the quality of a sampling scheme. Scientific data consist of randomly selected samples from larger populations. The purpose of the sample is to estimate the mean and so on of the population. A sample may mis-estimate the population mean as a result of bias or random sampling error. Bias is a predictable over or under-estimation, arising from poor experimental design. Random error arises due to the unavoidable risk that any randomly selected sample may over-represent either low or high values. The extent of random sampling error is governed by the sample size and the SD of the data.","is_dataset_classified":null,"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":"19965766","pmcid":null,"openalex_id":"https://openalex.org/W1411719529","authors":[],"funders":[],"total_grants":0,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[],"oa_status":"closed","license":null,"oa_locations":[{"url":"https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781119109075.ch5","host_type":"publisher"},{"url":"https://doi.org/10.1002/9781119109075.ch5","host_type":""}],"fields_of_study":["Meta-analysis and systematic reviews"],"mesh_terms":[],"keywords":["Statistics","Sampling (signal processing)","Sampling design","Sample size determination","Simple random sample","Sample (material)","Standard error","Systematic sampling","Population mean","Sampling bias","Standard deviation","Stratified sampling","Sampling error","Population","Random error","Mathematics","Observational error","Computer science","Demography"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"No poverty"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-13T18:49:38.257533Z","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":[]}