One of the greatest disadvantages of using range as a method of dispersion is that range is sensitive to outliers in the data. Range only considers the smallest and largest data elements in the set.
Continue ReadingIf outliers exist in a set of data such that the lowest or highest extremes are far away from almost every other data element in the set, then range may not be the best way to measure dispersion. For example, if one were to measure a student's consistency on quizzes, and he scored {40, 90, 91, 93, 95, 100} on six different quizzes, the range would be 60 points, marking considerable inconsistency. However, five of the six quizzes show consistency in the student's performance, achieving within 10 points of each other on all of these.
Using other methods of dispersion, such as measuring the interquartile range, the difference between the 25th and 75th percentile, provide a better representation of dispersion in cases where outliers are involved. Standard deviation and average deviation are also commonly used methods to determine the dispersion of data.
Learn more about StatisticsStandard deviation is a measure of the variation or diversity of scores in a set of data. It is used to determine how much data varies from the average of a population. The larger the deviation, the more spread out the data set. Standard deviation is represented by the Greek letter sigma.
Full Answer >A confidence interval for a statistical measure (range) is used to quantify the amount of uncertainty associated with a sample estimate of a population parameter. It is computed as Estimate ± Margin of Error. In a 95 percent confidence interval, for example, 95 percent of the samples are within the calculated population parameters.
Full Answer >In the field of math, data presentation is the method by which people summarize, organize and communicate information using a variety of tools, such as diagrams, distribution charts, histograms and graphs. The methods used to present mathematical data vary widely. Common presentation modes including coding data, data analysis, drawing diagrams, boxplots, tables, pie charts and histograms.
Full Answer >The interquartile range, or IQR, can be found after the median has been determined by dividing the data sets that are above and below the median in half, which divides the entire set into quarters, and then combining the second quarter with the third quarter. The resulting range is the IQR and represents the middle 50 percent of the entire data range. This splits the data set into three ranges, or quartiles: the first quartile (Q_{1}) is the 25 percent of the data range below the IQR, the third quartile (Q_{3}) is the 25 percent of the data range above the IQR and the IQR can be described as Q_{3} subtracted from Q_{1}.
Full Answer >