Yes.
An example: the data set {1, 1, 2, 2, 2, 2, 2, 2, 2, 3, 5} has median = Q1 = Q3 = 2.
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The median is Q2, if it is on the right side of the box, then then it is close to Q3 than it is to Q1. If the right line ( whisker) is longer than the left, it mean the biggest outlier is farther from Q3 than the smallest outlier is from Q1. All of this means the population from which the data was sampled was skewed to the right.
The quartile deviation(QD) is half the difference between the highest and lower quartile in a distribution.
It stands for the Inter-Quartile Range. Given a set of observations, put them in ascending order. The lower quartile (Q1) is the observation such that a quarter of the observations are smaller (and three quarters are at least as large). The upper quartile (Q3) is the observation such that a quarter are larger. [The middle one (Q2) is the median.] Then IQR = Q3 - Q1
The box represents your Q1, Q2 (median) and Q3, so it is your interquartile range. The Q1 is the first box line, the Q2 is the middle one and the Q3 is the closing line. Your interquartile range basically tells you where 50% of the people are.
For the numbers: 23 25 14 25 36 27 42 12 8 7 23 29 26 28 11 20 31 8 and 36 Q1=12 Q3=29 so IQR=29-12=17 If the second and third numbers are 2 and 5 and it is not 25 then it is 9.5 and28.5. Sadly this site still does not support commas in the questions so one cannot tell for sure. The two easy ways to find interquartile range or IQR are to either use a calculator like the TI 83, or by hand. By hand you find Q2 which is the median. That divides the data into two halves. Now Q1 is the median of the first half and Q3 is the median of the second half. Subtract Q1 from Q3 and you have IQR.