In the appropriate context, they do.
Mean.
Average. this is because the typical is what the total divided by the number of items. this is also what the mean (or average) is.
No, the variance is not defined as the mean of the sum of the squared deviations from the median; rather, it is the mean of the squared deviations from the mean of the dataset. Variance measures how much the data points differ from the mean, while the median is a measure of central tendency that may not accurately reflect the spread of the data in the same way. Though both concepts involve deviations, they use different points of reference for their calculations.
In a negatively skewed distribution, the mean is typically less than the median, and the median is less than the mode. This results in a tail that extends longer to the left. Therefore, any statement claiming that the mean is greater than the median or that the mode is less than the median would be false. Thus, one must be careful to identify which statements accurately reflect the characteristics of negatively skewed distributions.
For some kinds of distributions one, for others kinds, the other.
people or items chosen accurately reflect the group as a whole
When the mean and median do not coincide, it typically indicates that the data distribution is skewed. In a positively skewed distribution, the mean is greater than the median, while in a negatively skewed distribution, the mean is less than the median. This discrepancy arises because the mean is sensitive to extreme values, whereas the median is resistant to outliers, making it a better measure of central tendency in skewed distributions. Understanding this difference helps in accurately interpreting the data's characteristics.
The mean is the arithmetic average of a set of values, while the median is the middle value when the data is ordered. In symmetrical distributions, the mean and median are typically close or equal, but in skewed distributions, the mean can be influenced by extreme values, making it higher or lower than the median. Thus, the median is often preferred as a measure of center for skewed data, as it provides a better representation of the typical value without being affected by outliers.
The mean deviation from the median is equal to the mean minus the median.
NO mean: (average)add all the numbers, then divide by how many numbers you added!! Median: you have to put allthe numbers in order and then get the middle number and if there are two middle numbers add them and divide them by two!!
The three commonly used measures of central tendency are the mean, the median, and the mode. They are different ways of describing a "typical" member of the population.
In typical statistical distributions, these are measures that tend to lie close to the centre of the distribution.