There is not, so the question is misguided.
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.
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.
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.
To start, you need to identify the median of your set of data. After you have the median, split the remaining data into 2 groups, one with everything smaller than the median, one with everything larger. You then take the median of the 2 groups you just found in the previous step, the smaller one is called the first quartile and the larger one is called the 3rd quartile. Next, you have to find the smallest and largest numbers in the entire original set of data. Now, you should have 5 numbers, the minimum, 1st quartile, median, 3rd quartile, and maximum. To make our actual plot, you plot a scale along one axis and make a tick mark for each of the 5 values we found before. Then, create a line connection the minimum to the 1st quartile and the 3rd quartile to the maximum. Finally, connect the 1st quartile to the 3rd quartile with a rectangle and you're done! In addition, some plots add one more feature to make it easier to spot outliers. What they do is start by finding the difference between the 1st and 3rd quartile which is called the IQR (Inter-Quartile Range). Then, you see if every number less than the 1st quartile (and larger than the 3rd) is more than 1.5 times the IQR away. If it is, you remove the line going through any such values and place a little box at the point. Any place that gets a box can be called an outlier.