Meanlol
mean
Its the one most commonly used but outliers can seriously distort the mean.
The most appropriate measure of central tendency depends on the nature of the data. The mean is useful for normally distributed data without outliers, while the median is better for skewed distributions or when outliers are present, as it provides a more accurate representation of the central point. The mode is ideal for categorical data where we want to identify the most frequently occurring value. Therefore, the context and characteristics of the data should guide the choice of measure.
average is defined as a single value which has tendency to represent the data as a whole. averages are also called "measure of central tendency" or "measure of location"
Meanlol
mean
When there aren't extreme values (outliers)
Its the one most commonly used but outliers can seriously distort the mean.
Coefficient of Determination
The appropriate measure of central tendency for age is the median. This is because age is a continuous variable and can have outliers or extreme values, which can skew the mean. The median provides a more robust estimate of the center of the distribution.
Mean- If there are no outliers. A really low number or really high number will mess up the mean. Median- If there are outliers. The outliers will not mess up the median. Mode- If the most of one number is centrally located in the data. :)
Mode: Data are qualitative or categoric. Median: Quantitative data with outliers - particularly if the distribution is skew. Mean: Quantitative data without outliers, or else approx symmetrical.
the median is perferred when the data is strongly skewed or has outliers. =)
The mean is most affected. Mode and Median are not influenced as much by outliers.
The arithmatic mean is not a best measure for central tendency.. It is because any outliers in the dataset would affect its value thus it is considered not a robust measure.. The mode or median however would be better to measure central tendency since outliers wont affect it value.. Consider this example : Arithmatic mean dan mode from 1, 5, 5, 9 is 5.. If we add 30 to the dataset then the arithmatic mean will be 10 but the mode will still same.. Mode is more robust than arithmatic mean..
A weighted mean is probably best. Certainly better than a median which throws away information from most of the observations.