Download Data Quality Control. • Controlling for the quality of data collected from schools is a critical part of the data collection process. • Dat...
Download On consultant prepared design projects, Quality Control is the consultant's responsibility and generally Quality Assurance is the District's responsibility. • Consultant management has a QA responsibility for work performed in-ho
Download On consultant prepared design projects, Quality Control is the consultant's responsibility and generally Quality Assurance is the District's responsibility. • Consultant management has a QA responsibility for work performed in-ho
Download QA or provides limited QA inspection, half of the total quality management process is lost. Both QC and QA are necessary to ver- ify specification compliance and quality work, but an owner (or third-party inspector) performing QA on a
Download QA or provides limited QA inspection, half of the total quality management process is lost. Both QC and QA are necessary to ver- ify specification compliance and quality work, but an owner (or third-party inspector) performing QA on a
Download May 2001. Lab department. Quality control. Page 2. Protocol. • The expected values for the sensitivity and specificity: the expectation taken into account will be your last QC results. Use the following table to calculate the size of the
Download 12 May 2013 ... www.sciedu.ca/ijba. International Journal of Business Administration. Vol. 4, No. 3; 2013. Published by Sciedu Press. 61. ISSN 1923-4007 E-ISSN 1923-4015. Statistical Quality Control (SQC) and Six Sigma Methodology: An. A
Download Quality Control (QC) is the overall system of technical activities that measures the attributes and performance of a process, item, or service against defined standards to verify that they meet the stated requirements established by the
Download Quality Control (QC) is the overall system of technical activities that measures the attributes and performance of a process, item, or service against defined standards to verify that they meet the stated requirements established by the
Download Quality Control (QC) is the overall system of technical activities that measures the attributes and performance of a process, item, or service against defined standards to verify that they meet the stated requirements established by the
Download Digitization Quality Control Workflow. The level of quality control (QC) for digitization will vary based on the nature of the project and material being scanned. Typically, images will be processed at the proper resolution, cropped, a
Download Digitization Quality Control Workflow. The level of quality control (QC) for digitization will vary based on the nature of the project and material being scanned. Typically, images will be processed at the proper resolution, cropped, a
Download 12 May 2013 ... www.sciedu.ca/ijba. International Journal of Business Administration. Vol. 4, No. 3; 2013. Published by Sciedu Press. 61. ISSN 1923-4007 E-ISSN 1923-4015. Statistical Quality Control (SQC) and Six Sigma Methodology: An. A
Download Quality Control Narrative. 1. Describe the internal review procedures which facilitate high quality standards in the organization. QA performs process audits on components upon receipt of components from supply partners. During the man
Page 1 of 90 Minquan Electronics Chapter: 1.0 Promulgation Order Quality Manual Doc No.: QM-01 Chapter 1 Promulgation Order This Quality Manual is an outline of the
Download 12 May 2013 ... www.sciedu.ca/ijba. International Journal of Business Administration. Vol. 4, No. 3; 2013. Published by Sciedu Press. 61. ISSN 1923-4007 E-ISSN 1923-4015. Statistical Quality Control (SQC) and Six Sigma Methodology: An. A
Download May 2001. Lab department. Quality control. Page 2. Protocol. • The expected values for the sensitivity and specificity: the expectation taken into account will be your last QC results. Use the following table to calculate the size of the
Download Quality Assurance and Quality Control. Chapter 8. 8.2. IPCC Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories . CO-CHAIRS, EDITORS AND EXPERTS. Co-Chairs of the Expert Meeting on Cross-sectoral Met
Download Mobile optical 3D coordinate measuring technology is used for quality assurance on the production line in the BMW Regensburg plant. For the assembly of roof modules for convertibles, optical measuring equipment is used in process plann
Download Quality Assurance and Quality Control. Chapter 8. 8.2. IPCC Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories . CO-CHAIRS, EDITORS AND EXPERTS. Co-Chairs of the Expert Meeting on Cross-sectoral Met
DAMA-DMBOK Guide Goals. › To develop, build consensus and foster adoption for a generally accepted view of data management. › To provide standard definitions for data management functions, roles, deliverables and other common terminology. › To identi
Download Mobile optical 3D coordinate measuring technology is used for quality assurance on the production line in the BMW Regensburg plant. For the assembly of roof modules for convertibles, optical measuring equipment is used in process plann
Download Quality Assurance and Quality Control. Chapter 8. 8.2. IPCC Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories . CO-CHAIRS, EDITORS AND EXPERTS. Co-Chairs of the Expert Meeting on Cross-sectoral Met
Download QUALITY CONTROL. 8.1. INTRODUCTION. An important goal of IPCC good practice guidance is to support the development of national greenhouse gas inventories that can be readily assessed in terms of quality and completeness. It is good pra
Download QUALITY CONTROL. 8.1. INTRODUCTION. An important goal of IPCC good practice guidance is to support the development of national greenhouse gas inventories that can be readily assessed in terms of quality and completeness. It is good pra
Data Quality Control
Greg Keeble UNESCO Institute for Statistics
Overview • • • •
Data Quality Control Types of Data Quality Control Sources of data quality issues Roles & responsibilities for DQC
Data Quality Control • Controlling for the quality of data collected from schools is a critical part of the data collection process • Data need to be of high quality so that decisions can be made on the basis of reliable and valid data • A school census should collect relevant, comprehensive and reliable data about schools • Data collection system should use well-defined procedures and processes that apply data control measures to ensure the quality of the data
Data quality control measures Data control measures should apply at every stage of the data collection process: – School level – National, provincial and district levels Data quality control can be done: – before and during school census data collection – during data entry and processing – when analysing, interpreting and using the data
Types of Data Quality Control • Data Validation – Is the data right? – How valid is the data?
• Data Verification – Do we have the right data? – Can we rely on the data?
Data Validation Data validation is a process that follows prescribed rules about the value of data elements: – data type – range of values – missing values – consistency – total cross-referencing Data validation rules should enable correction of incorrectly entered data into EMIS or set an error flag for later follow-up
Data Verification Data Verification is a process in which different types of data are checked for accuracy and consistency after data entry is completed: – check totals for micro-data – reconciliation of data sources – previous year comparison – consistency with different data sets – data auditing processes Data verification should enable comparisons of aggregate data at each level of the education system, from schools, districts to national level
Sources of Data Quality Issues Main sources of data quality problems: – – – – –
School records Questionnaire and forms Concepts and definitions Data entry Checking processes
School records management Schools should: – apply records management standards and procedures – maintain school records in a systematic and rigorous manner
Quality information is needed for: – school management – school census questionnaire
Questionnaire Design Design the school census questionnaire: • to minimize socio-economic and cultural mis-understandings • with clear structure, presentation and explanations, and concise instructions. • based on feedback from testing and revise before finalizaton
Completing the questionnaire • School administrators must understand the instructions for completing the census questionnaire • School principals must carefully check and re-check the data for omissions and errors • District education officers should train Education Office Principal relevant school staff to complete the School questionnaire Admin
Data quality checks Data quality checks should be done as close to the data source as possible: At the school level, check: – data omissions – errors in calculations – inconsistencies in tables
At the district education office, check: – late or missing responses – misunderstanding among school managers – data omissions and errors
Data entry checks • Data validation should be incorporated into data entry systems using computers or online systems • Automatic data validation systems can signal any data omissions and errors on-screen so that corrections can be made immediately • Validation checks include: – blank or missing responses – out of range or invalid responses – inconsistent responses
Data analysis checks Unusual or unlikely data can be found during data analysis and interpretation: • Data verification checks calculate statistics to compare data between provinces, districts and schools • Data inconsistencies can be detected during the interpretation of analytical results • Data anomalies can be identified through an independent review of the analytical results
Roles and Responsibilities Different levels of the education administration have specific roles in the data quality control and assessment processes: – – – –
Schools Regional education offices Ministry of Education International agencies
Local Regional National International
Role of Schools Data quality control in schools is the role and responsibility of: • School inspectors are responsible for checking that the school has a system for managing school records • School principals are responsible for the accurate and complete completion of the school questionnaire • School administration staff are responsible for gathering and recording the data in the school records
Completing the questionnaire Errors may occur when data are being entered into the school census questionnaire due to: – mismatch between the data requirements and school records – mis-coding or mis-reporting of data – not checking responses to questions School Records
Census Questionnaire
Role of Regional Education Office The Regional Education Office is responsible for: • ensuring all the schools in the region receive the school census questionnaire and return the completed questionnaires in a timely manner. • providing assistance to schools to accurately complete the questionnaire • monitoring school records and helping schools to improve their school records management practices.
Regional Office checks Coverage check • Check that all schools have returned questionnaires • Contact and remind the schools that have not responded • Assist schools that have not completed the questionnaire Data check • Check all pages, questions and tables completed • Check explanations of data limitations • Check totals sum to the detailed data • Check the data is consistent in the questionnaire • Check for unusual or illogical data Feedback • Provide feedback to the Ministry of Education about difficulties encountered during the school census.
Role of Ministry of Education The Ministry of Education is responsible for • designing, pre-testing and producing the school census questionnaire to collect data from the schools. • maintaining register of schools and logging receipt of completed questionnaires from schools • data processing of collected data into the EMIS system, including data entry and validation
Practical Exercise • Develop rules for data validation and verification of your EMIS dataset • Perform a data validation of your EMIS dataset • Perform a data verification of your EMIS dataset