That median is the value separating the higher half of a data sample, a population, or a probability distribution, from the lower half. For a data set, it may be thought of as the "middle" value. For example, in the data set {1, 3, 3, 6, 7, 8, 9}, the median is 6, the fourth largest, and also the fourth smallest, number in the sample. For a continuous probability distribution, the median is the value such that a number is equally likely to fall above or below it. 

The median is a commonly used measure of the properties of a data set in statistics and probability theory. The basic advantage of the median in describing data compared to the mean (often simply described as the "average") is that it is not skewed so much by extremely large or small values, and so it may give a better idea of a "typical" value. For example, in understanding statistics like household income or assets which vary greatly, a mean may be skewed by a small number of extremely high or low values. Median income, for example, may be a better way to suggest what a "typical" income is. 

Because of this, the median is of central importance in robust statistics, as it is the most resistant statistic, having a breakdown point of 50%: so long as no more than half the data are contaminated, the median will not give an arbitrarily large or small result. QUESTIONS:

Q1:
1. What is a fundamental element of robust statistics?
2. What is vital to robust statistics?
3. 
Q2:
1. What does the median measure?
2. What is metered out by the median?
3. 
Q3:
1. What is the median a data set inside of?
2. What is median a data set contained within?
3. 
Q4:
1. What are the benefits of using median?
2. What is helpful about measuring a median?
3. 
Q5:
1. What isn't the median skewed by?
2. What is not something that influences the median greatly?
3. 
Q6:
1. What are the benefits of using median other than not being skewed by extremes?
2. What is helpful about measuring a median, in addition to not being impacted by extremes?
3. 
Q7:
1. What can put a mean off balance?
2. What factor can skew the mean?
3. 
Q8:
1. Does robust statistics consider the median to be the most resistant statistic?
2. Is the statistic with maximum resistance in robust statistics the mean?
3. 
Q9:
1. What explanation is given of a median in continuous probability distribution?
2. What is the deifnition of a median within a continuous probability distribution?
3. 
Q10:
1. What is the median within a data set?
2. How is the median defined inside of a data set?
3. 
Q11:
1. What is the breakdown point of the median in robust statistics?
2. Where does the median breakdown in robust statistis?
3. 
Q12:
1. What cannot happen to more than half the data in robust statistics?
2. What must not occur with over half the data?
3. 
Q13:
1. What happens if more than 50% of data is contaminated?
2. What occurs in the event of contamination of over half the data?
3. 
