{"id":5169,"date":"2018-03-09T14:20:39","date_gmt":"2018-03-09T19:20:39","guid":{"rendered":"http:\/\/easinc.org\/wordpress\/?page_id=5169"},"modified":"2018-08-09T17:58:22","modified_gmt":"2018-08-09T21:58:22","slug":"setting-data-quality-objectives-determining-reporting-interpreting-data-quality-indicators-meet-scholarly-publication-requirements","status":"publish","type":"page","link":"https:\/\/eas.org\/2024\/setting-data-quality-objectives-determining-reporting-interpreting-data-quality-indicators-meet-scholarly-publication-requirements\/","title":{"rendered":"E18-31: Setting Data Quality Objectives and Determining, Reporting, and Interpreting Data Quality Indicators to Meet Scholarly Publication Requirements"},"content":{"rendered":"
\n

One-Day Course<\/strong><\/em><\/span>\u00a0
Tuesday, Nov. 13; 8:30am – 5:00pm<\/strong><\/em>
\n<\/em><\/p>\n<\/div>\n

Dr. Ephraim M. Govere, Pennsylvania State University, State College, PA<\/p>\n

COURSE DESCRIPTION<\/span>
\n<\/b>At Universities and government, non-government, and private research organizations, the number of peer-reviewed publications is a key performance indicator for promotion, maintaining, or securing a job.\u00a0 This course gives an overview of the necessary actions to be taken to make sure that analytical data of known quality objectives are obtained to meet scholarly publication requirements by high impact scientific journals. \u00a0Research article publication acceptance rate in high impact journals can be enhanced by proper setting of data quality objectives and determining, reporting, and interpreting data quality indicators. \u00a0Some of the data indicators used to demonstrate quality of research results are: reported accuracy, precision, recovery, detection limits, and sensitivity.<\/p>\n

WHO SHOULD ATTEND<\/span>
\n<\/b>This one-day course will benefit assistant professors, graduate students, postdocs, research associates, and research technicians.<\/p>\n

TOPICS
\n<\/b>1. Accuracy of Analytical Methods
\n2. Analytical Bias
\na. Serious bias
\nb. Acceptable bias
\nc.\u00a0Insignificant bias
\n3. Measurement Sensitivity
\na. Calibration sensitivity
\nb. Analytical sensitivity
\nc. Sensitivity, bias, and uncertainty interval
4. Measurement Precision
\na. Reproducibility
\nb. Repeatability
\n5. Recovery
\na. Recoveries for assessing calibration sensitivity and analysis sensitivity
\u00a0 \u00a0 \u00a0b. Recoveries for determining whether the sample matrix affects accuracy
\u00a0 \u00a0 \u00a0c. Recoveries for correcting bias
\n6. Detection Limits
\na.\u00a0Limit of detection (LOD)
\nb.\u00a0Method detection limit (MDL)
\nc.\u00a0 Instrument detection limit (IDL)
\nd.\u00a0Limit of quantification (LOQ)
\n7.\u00a0Setting Data Quality Objectives and Reporting Data Quality Indicators in Research Journals<\/p>\n

<\/a>ABOUT THE INSTRUCTOR<\/span>
\n<\/b>Dr. Ephraim Muchada Govere <\/strong>is a laboratory director at The Pennsylvania State University (PSU).\u00a0 He directs and manages a multi-function, multi-user research cluster laboratory that provides leadership, expertise, and analytical instrumentation and equipment necessary for research and teaching in the areas of environmental and agricultural chemistry.\u00a0 Dr. Govere has national and international analytical experience that includes working for Dynamac International Corporation Environmental Services at the USA West Ecology Division EPA Environmental Research Laboratory, and at the International Fertilizer Development Center.<\/p>\n","protected":false},"excerpt":{"rendered":"

One-Day Course\u00a0Tuesday, Nov. 13; 8:30am – 5:00pm Dr. Ephraim M. Govere, Pennsylvania State University, State College, PA COURSE DESCRIPTION At Universities and government, […]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-5169","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/eas.org\/2024\/wp-json\/wp\/v2\/pages\/5169"}],"collection":[{"href":"https:\/\/eas.org\/2024\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/eas.org\/2024\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/eas.org\/2024\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/eas.org\/2024\/wp-json\/wp\/v2\/comments?post=5169"}],"version-history":[{"count":7,"href":"https:\/\/eas.org\/2024\/wp-json\/wp\/v2\/pages\/5169\/revisions"}],"predecessor-version":[{"id":5667,"href":"https:\/\/eas.org\/2024\/wp-json\/wp\/v2\/pages\/5169\/revisions\/5667"}],"wp:attachment":[{"href":"https:\/\/eas.org\/2024\/wp-json\/wp\/v2\/media?parent=5169"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}