04:37
Faizan
Overview
Once more I have to apologise in advance to any statistics experts. In a previous article we explored basic statistics terminology and went over the mean or expected value of a set of determined values. Here, we increase this to the median, mode, variance and the useful standard deviation. I hope, this article will offer people a bit extra familiarity with the following terms.
Median:
In the former article we checked out the 'expected value' or 'mean' of a set of values that we may measure. These were:
Values: 3, 5, 5, 6, 7, 9, 10, 11, 12, 12, 15, 16
Usually, measured values would have a random sequence but the values above have been sequenced from low to high.
The median value is that value at the center of the sequence that has 50 % of the values larger and 50 percent of its values lower.
In the occurrence above there isn't a 'center' value since we hold twelve values. Thus, we pick the 2 central values of 9 and 10 and average them to get 9.5. This is then the median value.
If we used the values: 3, 5, 5, 6, 7, 9, 9, 10, 11, 12, 12, 15, 16, the center value (of a total of 13) would be 9 as the median value.
Anytime values change a great deal the median can be useful as a tool that smoothes out the data. It can serve to track movements in the data by recording the median values. Data values can then be viewed as a deviation from the median and may provide a notion whether it is migrating outside this trend.
Whenever the median value is exactly the same as the mean or expected value then there is a balanced distribution of values. Whenever the median is larger or smaller than the mean or expected value, then the distribution of the values will be slanted either to the left or right.
Mode:
Anytime it comes to basic statistics terminology this is simple. If we again check out the above values measured and alter one of them to 12 from 15 we get:
Once more I have to apologise in advance to any statistics experts. In a previous article we explored basic statistics terminology and went over the mean or expected value of a set of determined values. Here, we increase this to the median, mode, variance and the useful standard deviation. I hope, this article will offer people a bit extra familiarity with the following terms.
Median:
In the former article we checked out the 'expected value' or 'mean' of a set of values that we may measure. These were:
Values: 3, 5, 5, 6, 7, 9, 10, 11, 12, 12, 15, 16
Usually, measured values would have a random sequence but the values above have been sequenced from low to high.
The median value is that value at the center of the sequence that has 50 % of the values larger and 50 percent of its values lower.
In the occurrence above there isn't a 'center' value since we hold twelve values. Thus, we pick the 2 central values of 9 and 10 and average them to get 9.5. This is then the median value.
If we used the values: 3, 5, 5, 6, 7, 9, 9, 10, 11, 12, 12, 15, 16, the center value (of a total of 13) would be 9 as the median value.
Anytime values change a great deal the median can be useful as a tool that smoothes out the data. It can serve to track movements in the data by recording the median values. Data values can then be viewed as a deviation from the median and may provide a notion whether it is migrating outside this trend.
Whenever the median value is exactly the same as the mean or expected value then there is a balanced distribution of values. Whenever the median is larger or smaller than the mean or expected value, then the distribution of the values will be slanted either to the left or right.
Mode:
Anytime it comes to basic statistics terminology this is simple. If we again check out the above values measured and alter one of them to 12 from 15 we get:
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