Mean, Median, Mode and Range
Understanding Mean, Median, Mode and Range
- Mean is the average of a set of data. It is calculated by summing all the data values and then dividing by the number of values.
- The Median represents the middle value in an ordered data set. When the data set has an odd number of observations, the median is the middle number. When there’s an even number of observations, it’s the average of the two middle numbers.
- The Mode is the value that appears most frequently in a data set. A set of data may have one mode, more than one mode, or no mode at all.
- Range provides a measure of how spread apart the values are in a data set. It is calculated by subtracting the smallest value in the set from the largest value.
Practical Applications of Mean, Median, Mode and Range
- The mean is used when you want to determine the average value of a data set, such as calculating average grades or average income.
- Median is particularly useful when you are dealing with data that is skewed or has outliers. It gives the central tendency of the data without being affected by extreme values.
- The mode is useful when the most common item, characteristic, or value of a data set needs to be found.
- The range can give a quick sense of the spread of values, although it’s sensitive to outliers.
Calculating Mean, Median, Mode and Range
- To calculate the mean, add up all the values and then divide by the count of values.
- To find the median, list the values in numerical order and locate the value in the middle. If there’s an even number of values, find the mean of the middle two.
- The mode is simply the value that appears most often.
- To calculate the range, subtract the smallest value from the largest value in the data set.
Deeper Understanding of Mean, Median, Mode and Range
- The mean is the only measure of central tendency where all the values in the data set are used.
- Be mindful that the median might not be one of the values in the data set if the total number of values is even.
- The mode does not provide information about the centre of the distribution and can be misleading with sparse data or many modes.
- Remember, a small range can still have outliers and does not tell you if the data is clustered around the mean or spread out across the available range.