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The upper quartile, for a set of ordinal observations, is a value such that a quarter of the observations have a greater value. Similarly, the lower quartile is a value such that a quarter of the observations have a smaller value.
In a set of observations it is a value such that 10% of the observations are smaller than the value and 90% are larger. One or both inequalities may be inclusive.
Do bees fly faster before or after eating
The quartiles for a set of data are three values - the lower quartile, the median and the upper quartile - such that they divide the data set into four parts with an [approximately] equal number of observations in each. Thus:a quarter of all the observations are smaller than the lower quartile,a quarter of all the observations are between the lower quartile and the median,a quarter of all the observations are between the median and the upper quartile, anda quarter of all the observations are greater than the upper quartile.The quartiles for a set of data are three values - the lower quartile, the median and the upper quartile - such that they divide the data set into four parts with an [approximately] equal number of observations in each. Thus:a quarter of all the observations are smaller than the lower quartile,a quarter of all the observations are between the lower quartile and the median,a quarter of all the observations are between the median and the upper quartile, anda quarter of all the observations are greater than the upper quartile.The quartiles for a set of data are three values - the lower quartile, the median and the upper quartile - such that they divide the data set into four parts with an [approximately] equal number of observations in each. Thus:a quarter of all the observations are smaller than the lower quartile,a quarter of all the observations are between the lower quartile and the median,a quarter of all the observations are between the median and the upper quartile, anda quarter of all the observations are greater than the upper quartile.The quartiles for a set of data are three values - the lower quartile, the median and the upper quartile - such that they divide the data set into four parts with an [approximately] equal number of observations in each. Thus:a quarter of all the observations are smaller than the lower quartile,a quarter of all the observations are between the lower quartile and the median,a quarter of all the observations are between the median and the upper quartile, anda quarter of all the observations are greater than the upper quartile.
It is the value, in the distribution of a variable, such that 25% (or a quarter) of the observations are smaller than it.
The first quartile, or the lower quartile, is the value such that a quarter of the observations are smaller and three quarters are larger.The third quartile, or the upper quartile, is the value such that three quarters of the observations are smaller and a quarter are larger.
Quartiles in statistics are three values such that the lower quartile, second quartile (better known as the median) and upper quartile divide up the set of observations into four subsets with equal numbers in each subset.a quarter of the observations are smaller than the lower quartile,a quarter of the observations are between the lower quartile and the median,a quarter of the observations are between the median and the upper quartile, anda quarter of the observations are greater than the upper quartile,
It is the value of the variable such that 40 percent of observations are smaller and 60 percent are larger.
It is a value such that a quarter of the observations are smaller than it and three quarters are larger.
The first decile (D1) is a number such that one tenth of the observations are smaller and nine tenths are larger. The ninth decile (D9) is a number such that nine tenths of the observations are smaller and one tenth are larger. The interdecile range is D9 - D1
The interquartile range (IQR) is a measure of spread in statistics. The observations (data) are arranged in order of magnitude - usually smallest to largest.Suppose there are n observations. Then calculate (n+1)/4 and round it to m, say. For large n (>30) don't bother with the +1 Then find the values of the observations is positions m and 3m. [That last sentence would be so much simpler if this crap browser allowed superscripts but mth and 3mth is confusing!] The number in position m is called the "Lower Quartile" and a quarter of the observations are smaller than it is. The number in position 3m is called the "Upper Quartile" and a quarter of the observations are greater than it is. The difference between the two values (not m and 3m but the values of the observations in those positions) is the IQR.Since a quarter of the observations are smaller than the LQ and a quarter are larger than the UQ, the IQR contains the middle half of all observations.
The naive answer to the question is 30. That assumes that the observations are more or less uniformly distributed across the range and, if that is the case, you should get around 5 observations per class. It also assumes that your interest in the observations is uniform: you are as interested in values near 60 as you are in values near 480. If you were only really interested in values above 450, you could class all of 56 to 449 in one big class and split the rest into smaller classes. It is also important to see if the distribution is uniform. If it is skewed in either direction, it would make more sense to have smaller classes where the observations were more dense and wider classes where they were sparse.