The question is how do the mean and median affect the distribution shape.
In a normal curve, the mean and median are both in the same point. ( as is the mode)
If a distribution is skewed, its tail is either on the right or the left.
If a distribution is skewed the median may be a better value to use than the mean since it has less effect on the shape. Also is there are large outliers, the median has less effect and is better to use.
So the mean has a bigger effect on the shape many times than the median.
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What is the answer
yes they are if you have 0 and 10 the mean is 5 and so is the median. The mean and the median can in fact be the same value. But basically to answer your question, One possible way is that if the values are ascending by 1 in the data set, then the number of values left to the median should be the same as the number of values right to the median. e.g. 6+7+8+9+10 6,7 = 2 terms 9,10 = 2 terms median =8 mode = 8
The MEDIAN is the number in the middle. In order to find the median, you have to put the values in order from lowest to highest, then find the number that is exactly in the middle. For example : 80 85 90 90 90 100 ^ since there is an even number of values, the MEDIAN is between these two, or it is 90. Notice that there is exactly the same number of values above the median as below it! Its that simple.
The mean (average value), the median (middle value), and the mode (most frequently occurring value) are all important values.
Generally, when the median is greater than the mean it is because the distribution is skewed to the left. This results in outliers or values further below the median than above the median which results in a lower mean value than median value. When a distribution is skewed left, it is generally not very symmetrical or normally distributed.