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The interquartile range is used as a measure of variability to overcome what difficulty of the range?

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2012-02-15 03:21:07
2012-02-15 03:21:07

the range influences the extreme

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Generally, the standard deviation (represented by sigma, an O with a line at the top) would be used to measure variability. The standard deviation represents the average distance of data from the mean. Another measure is variance, which is the standard deviation squared. Lastly, you might use the interquartile range, which is often the range of the middle 50% of the data.


Yes. The greater the range, the greater the variability.


The interquartile range is well known as a measure of statistical dispersion. It is equal to difference between upper and lower quartiles. The quartiles is a type of quantile.


It is important in any statistic measure


The interquartile range is less likely to be distorted by outliers (extreme values).


The semi interquartile range is a measure for spread or dispersion. To find it you have to subtract the first quartile from Q3 and divide that by 2, (Q3 - Q1)/2


The interquartile range is the upper quartile (75th percentile) minus (-) the lower percentile (75th percentile). The interquartile range uses 50% of the data. It is a measure of the "central tendency" just like the standard deviation. A small interquartile range means that most of the values lie close to each other.


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Variability is a measure of differences between multiple observations. These may be observations of a number of different objects or repeated observations on the same object.


The IQR gives the range of the middle half of the data and, in that respect, it is a measure of the variability of the data.


Which measure of variability is the most appropriate for this set of values?13, 42, 104, 36, 28, 6, 17


It is a measure of how much a measure [of a variable] can change.


The standard deviation is the value most used. Others are variance, interquartile range, or range.


It measures the error or variability in predicting Y.


If the raw math scores are available for all of the students then you could probably apply a t test to the results. Alternatively you could use a Wilcoxon rank sum test. The difficulty you face is that, without a measure of the variability in the scores you cannot be sure that the difference in the means is due to actual difference or just variability. To get that measure you need th raw scores.


The interquartile range (IQR) is a measure of variability, based on dividing a data set into quartiles. Quartiles divide a rank-ordered data set into four equal parts.


It is a measure of the spread of a set of observations. It is easy to calculate and is not distorted by extreme values (or mistakes). On the other hand it does not use all of the information contained in the data set.


The answer lies in the question! The first lot measure where the centre of a distribution or observation lies while the second lot are a measure of the distance of individual observations from the centre.


standard deviation is the square roots of variance, a measure of spread or variability of data . it is given by (variance)^1/2


The measure of variability tells you how close to the central value the data values lie: that is whether the cluster is tightly packed around the central value of spread out over a large range of values.


With great difficulty. A kilometre is a measure of distance whereas a degree Celsius is a measure of change in temperature. There is no relationship between the two.


If an object is at rest it has inertia, which has to be overcome to make it move. When an object is moving in a straight line at a constant speed it has momentum, which must be overcome to slow or stop the object


You can take half of the rate of variability and measure it against lightyears to get the maximum distance.It means that if it takes half a minute to complete the full brightness,the source cannot be brigger than half a lightminute across


Standard deviation is a commonly used measure of the variability of a set of measurements.But that usually refers to a 'normal' distribution - an assumption that the results are distributed according to a 'normal' (Gaussian) curve. There are several other types of distribution, Poisson, Bernoulli, and others.It is important to note that the application of standard deviation becomes less and less useful as one approaches the extremes of the set of measurements.


that which is either two or three standard deviations (a statistical measure of variability) below the normal average head circumference for the age, gender, and race of the child.



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