We are receiving a lot of questions about relevant analyses in the Analyse-it Method Validation edition to help in evaluating new diagnostic tests in the fight against COVID-19. Below are some quick links that will help, but contact us if you have questions - we are working as normal.
Also see our latest blog post: Sensitivity/Specificity and The Importance of Predictive Values for a COVID-19 test
A box plot shows the five-number summary of the data – the minimum, first quartile, median, third quartile, and maximum. An outlier box plot is a variation of the skeletal box plot that also identifies possible outliers.
An outlier box plot is a variation of the skeletal box plot, but instead of extending to the minimum and maximum, the whiskers extend to the furthest observation within 1.5 x IQR from the quartiles. Possible near outliers (orange plus symbol) are identified as observations further than 1.5 x IQR from the quartiles, and possible far outliers (red asterisk symbol) as observations further than 3.0 x IQR from the quartiles. You should investigate each possible outlier before deciding whether to
exclude it, as even in normally distributed data, an outlier box plot identifies approximately 0.7% of observations as possible outliers.