Rating Slam Dunks to Visualize the Mean, Median, Mode, Range, and Standard Deviation

comparison of estimators of standard deviation, mean moving range and median moving range to estimate process standard deviation using autocorrelated data

independence of observations is a fundamental assumption in designing an x chart for individual observations. but unfortunately, the assumption of existence of independent data is not even approximately satisfied. in fact, there is one kind of autocorrelation in the data. this paper demonstrates, through simulating an ar(1) process, that the autocorrelation in the data has deep effect on x char...

Mean Anisocoria ± Standard Deviation ( Range ) ( mm )

69 ABSTRACT PURPOSE: To report the incidence of anisocoria after unilateral excimer laser photorefractive kera-tectomy (PRK) for myopia and subsequent cortico-steroid therapy in a retrospective and prospective study and to explore possible etiologies. METHODS: The horizontal pupil diameter was determined in 6 patients (6 eyes) at 21.8 ± 12.6 months after unilateral wide-field excimer laser PRK ...

Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range

BACKGROUND In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard...

Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median

Approximate Range Mode and Range Median Queries

We consider data structures and algorithms for preprocessing a labelled list of length n so that, for any given indices i and j we can answer queries of the form: What is the mode or median label in the sequence of labels between indices i and j. Our results are on approximate versions of this problem. Using O( n 1−α ) space, our data structure can find in O(log log 1 α n) time an element whose...