An outlier.
the interquartile is just subtracting the high quartile from the low quartile. * * * * * No, it is subtracting the lower quartile from the higher quartile.
It is affected by all that goes on in the conurbation. Temperatures in towns are significantly higher than surrounding countryside.
The cumulative frequency curve is shaped like an S. The lower quartile is 1/4 the way up on the cumulative frequency axis. The upper quartile is 3/4 the way up on the cumulative frequency axis The inter-quartile range is the upper quartile minus the lower quartile as plotted on the horizontal axis. Further details can be found in a higher level maths text book.
an outlier can be found with this formula... Q3-Q1= IQR( inner quartile range) IQR*1.5=x x+Q3= anything higher than this # is an outlier Q1-x= anything smaller than this # is an outlier
lower quartile = 1/4(n+1) upper quartile = 3/4(n+1) where n is the number of the values. Obviously the values have to be ordered from the lower to the higher: the number you'll get is the position in this order. Let's say you get 4 for your lower quartile, it means that the 4th value is your lower quartile.
Yes. If the predominant data are higher than the median, the mean average will be higher than the median average. For example, the median average of the numbers one through ten is five. The mean average is five and one-half.
Yes. It can be higher or lower
it is a divison
Yes. If you have very high or very low outliers in your data set, it is generally preferred to use the median - the mid-point when all data points are arranged from least to greatest. A good example for when to avoid the mean and prefer the median is salary. The mean is less good here as there are a few very high salaries which skew the distribution to the right. This drags the mean higher to the point where it is disproportionately affected by the few higher salaries. In this case, the median would only be slightly affected by the few high salaries and is a better representation of the whole of the data. In general, if the distribution is not normal, the mean is less appropriate than the median.
Yes, the median can be greater than the mean. It just depends on the values of the data. A simple series of 1,5,6 has 5 as the median, with a mean of 4.
If you order the numbers from the higher to the lowest, the median is the number separating the lower half of the numbers from the higher half of the numbers in the set. If you have an odd number of elements in the set then the median is in the middle of this descending ordered numbers. If you have an even number of elements then, in order to determine the median, you calculate the mean of the two middle values.
Managers often quartile key performance indicators to improve results. Focusing on eliminating dispersion brings your low performers higher. Key performance indicators used could be employee efficiency, process improvement analysis and many others.