There is not, so the question is misguided.
The second quartile, also known as the median, is equal to the median of a dataset. It represents the value that divides the data into two equal halves, meaning that 50% of the data points fall below it and 50% fall above it. Therefore, the second quartile is neither more nor less than the median; they are the same.
25% of the observed values are smaller than the lower quartile.
The value of any element in the third quartile will be greater than the value of any element in the first quartile. But both quartiles will have exactly the same number of elements in them: 250.
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.
These are sometimes considered outliers but there is no formal definition for them.
The second quartile, also known as the median, is equal to the median of a dataset. It represents the value that divides the data into two equal halves, meaning that 50% of the data points fall below it and 50% fall above it. Therefore, the second quartile is neither more nor less than the median; they are the same.
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,
25% of the observed values are smaller than the lower quartile.
The first quartile is the value such that a quarter of the data are smaller than that value and three quarters are larger. Since there are 8 observations, the quartile will be between the second and the third smallest values. Therefore, Q1 = (7+15)/2 = 11
What is mean deviation and why is quartile deviation better than mean deviation?
The value of any element in the third quartile will be greater than the value of any element in the first quartile. But both quartiles will have exactly the same number of elements in them: 250.
Because the IQR excludes values which are lower than the lower quartile as well as the values in 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.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.
These are sometimes considered outliers but there is no formal definition for them.
You arrange the data set in ascending order. You then find the observation such that a quarter of the observations are smaller than it and three quarters are bigger. That value is the lower quartile. Next find the observation such that three quarters of the observations are smaller than it and a quarter are bigger. That value is the upper quartile. Upper quartile minus lower quartile = IQR.
The median is the middle value in a dataset when it is sorted in ascending order. It divides the data into two equal parts. Quartiles, on the other hand, divide a dataset into four equal parts. The first quartile (Q1) is the median of the lower half of the data, the second quartile (Q2) is the median of the entire dataset (same as the median), and the third quartile (Q3) is the median of the upper half of the data.
It means that the smaller value (in the lowest quartile) are more spread out than larger values.