The Assumption of NO OUTLIERS in Parametric Hypothesis Tests (16-4) скачать в хорошем качестве

The Assumption of NO OUTLIERS in Parametric Hypothesis Tests (16-4)

Parametric statistical tests require that the dependent variable does not contain unusual or extreme scores. Univariate outliers can be detected using z-scores. The nature of the outlier determines how you should correct it. Multivariate outliers are identified with a Mahalanobis test; you must delete multivariate outliers. Chapters 0:00 No unusual or extreme scores 0:50 Univariate outliers 1:19 Winsorize outliers 2:12 Multivariate outliers ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ This video is part of a series for an introductory statistics course. It supports an academic course QBA 237 Basic Business Statistics at Missouri State University, College of Business, Department of Information Technology and Cybersecurity. Posted beginning in August 2022. This series was designed, written, produced, recorded, edited, and posted by Dr. Todd Daniel, a Ph.D. statistician and researcher with extensive experience in academic statistical research and statistics instruction. Dr. Daniel directed a research institute for many years before doing private consulting for Research by Design, LLC. He remains active in teaching and research. ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ Statistics Instructors: you are free to link to this video and the playlist for your seated or online statistics course or for other educational purposes. Edited in Camtasia 2022 Visual and audio content from DigitalJuice.com Music: Digital Juice Royalty Free Music ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ Link to a Google Drive folder with any files that I use in the videos. https://drive.google.com/drive/folder... To download, hover your cursor over the file icon and a blue download icon will appear. You do not need to request access to a file.