How to Handle Outliers in your Dataset in Business Statistics (Week 6B)

Outliers can cause big problems in your data. We learn what causes outliers, how to identify them, the problems they cause, and options for dealign with them. Some outliers should stay in the data. Others should be corrected, winsorized, or sometimes discarded. We explore the difference between univariate outliers and multivariate outliers, when they occur, and what to do about them. Dr. Daniel uses Excel to show you how to identify outliers using z-scores. All examples use the DogToys2.xlsx (link below) Lecture date: Tuesday, February 16, 2021 Missouri State University Snow day - lecture recorded at home office 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 2020 Visual and audio content from DigitalJuice.com Music: 248609_theBlues_15_Standard Source: Digital Juice Royalty Free Music Link to a Google Drive folder with any files that I use in the videos including spreadsheets, the Bear Handout, and the DogToys2.xlsx dataset. As I add new files, they will appear here, as well. 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.