У нас вы можете посмотреть бесплатно Data Management: Data Quality Control или скачать в максимальном доступном качестве, видео которое было загружено на ютуб. Для загрузки выберите вариант из формы ниже:
                        Если кнопки скачивания не
                            загрузились
                            НАЖМИТЕ ЗДЕСЬ или обновите страницу
                        
                        Если возникают проблемы со скачиванием видео, пожалуйста напишите в поддержку по адресу внизу
                        страницы. 
                        Спасибо за использование сервиса ClipSaver.ru
                    
This presentation on ‘Data Quality Control’ was recorded on 2022, February 14th as Session 1 of Module 2 of the Data Management course delivered by Statistics for Sustainable Development, and covers common data quality issues. This session was presented by Ciara McHugh. This course was supported by the Global Collaboration for Resilient Food Systems. For our free resources, visit our website: https://stats4sd.org/resources The other sessions in this module are here: • Data Management in Practice (Module Two) Mira este video en español: • Gestión de datos: Control de calidad de lo... Statistics for Sustainable Development is a not-for-profit, social enterprise that provides: • Statistical and data management expertise • Support on research designs and methodology • Technical guidance related to collection and processing of data and information. As a team of technicians and statisticians, we believe that our best work is done when supporting organisations and communities across the world that share our vision of a more sustainable future for all. The videos on our channel aim to support students, researchers, and academics, and are accompanied by the free resources on our website. Stay updated on what the team is up to over on our LinkedIn: / statistics-for-sustainable-development Contents: 00:00 - Intro 01:02 - Data Quality Control Workflow 01:48 - Common Data Issues 02:44 - Completeness of Data 05:09 - Location Data 06:55 - Duplicates 07:31 - Incorrect Observations 08:05 - Data Types 08:43 - Missing Values 09:07 - Different Levels of Data 09:57 - Units of Measurement 11:01 - Categorical Data Text Formatting 12:29 - Contradicting Values 13:15 - Documentating Data Quality