the median is the middle value of a set of numbers. Thus if you wanted to find the median of a group of numbers, you can organize them in numerical order, and find which is the middle term (if it is an even set of numbers, in which you have two middle numbers, add the two together and than divide it by 2).
no.
Median cannot be used for qualitative data (a mode can).The sampling distribution of the median is complicated (the mean is well studied).Median can usually be used for data that can be ordered without there being a ratio scale. For example, "small-medium-large", or "very negative-negative-neutral-positive-very positive". A mean cannot be calculated without arbitrarily assigning a numerical value to the terms.A median is not dependent on all the values which means that it is not distorted by outliers (extreme values).It is easy to find the median value from cumulative frequency charts.
The median is 5.The median is 5.The median is 5.The median is 5.
The median is 28.The median is 28.The median is 28.The median is 28.
The median is 19, although finding the median of a single value is a pointless exercise.
no.
No.
The median can be calculated using the Median function. Assuming the values you wanted the median of were in cells B2 to B20, you could use the function like this: =MEDIAN(B2:B20)
No. The mean and median are not necessarily the same. They will be the same if the distribution is symmetric but the converse is not necessarily true. That is to say, a distribution does not have to be symmetric for the mean and median to be the same. For example, the mean and median of {1, 1, 5, 6, 12} are both 5 but the distribution is NOT symmetric.
It might not be statistically representative of the population. However, the sample median can still be calculated as the value which is equal to or greater than half of the population.
Deviations are calculated from some value: the mean, the median, the maximum or whatever. You subtract that value from each observed value.
Ah, the median and the midpoint are both ways to find the middle of a set of numbers, but they are calculated differently. The median is the middle number when the numbers are ordered from least to greatest, while the midpoint is the exact middle point between two endpoints. Both are beautiful ways to find balance and harmony in our mathematical landscapes.
Median cannot be used for qualitative data (a mode can).The sampling distribution of the median is complicated (the mean is well studied).Median can usually be used for data that can be ordered without there being a ratio scale. For example, "small-medium-large", or "very negative-negative-neutral-positive-very positive". A mean cannot be calculated without arbitrarily assigning a numerical value to the terms.A median is not dependent on all the values which means that it is not distorted by outliers (extreme values).It is easy to find the median value from cumulative frequency charts.
The median is 5.The median is 5.The median is 5.The median is 5.
It is calculated the same way as if there were an odd number of numbers:mean = sum of all the numbers ÷ how many numbers there areThe median however is calculated slightly differently. After the numbers have been sorted into order, then:If there is an odd number of numbersThe median is the middle one which is the ((number_of_numbers + 1)÷2)th one. eg if there are 15 numbers this is the ((15+1)÷2)th = 8th number.If there is an even number of numbersThe median is given by the mean of the middle two numbers. eg if there are 20 numbers, then the median is the mean of the (20÷2)th = 10th and the (20÷2+1)th = 11th numbers, ie the median is (10th number + 11th number)÷2
No. The mean is calculated by adding all of the numbers, then dividing that sum by [how many numbers]. The trimmed meandoes remove some outliers (same number of outliers at top and bottom, though). The median is the middle number of a sorted set.
First, I will give an example, similar to your question: -11000 -9000 +44000 mean = 8,000 and median = -9000. Symmetrical distributions after infinite sampling will show no difference in mean and median. Large differences are possible with small sample sizes even with symmetrical distributions. If the sample is large and the difference is large, this infers that the distribution is asymmetrical. The skewness of the distribution can be calculated.