Their mathematical formulation is also well known along with their associated stereotypical examples (e.g., harmonic mea. What does it imply for standard deviation being more than twice the mean Our data is timing data from event durations and so strictly positive (sometimes very small negatives show up due to clock The distribution of the mean difference should be tighter then the distribution of the difference of means See this with an easy example
1 10 100 1000 mean in sample 2 2 11 102 1000 difference of means is 1 1 2 0 (unlike samples itself) has small std. The mean is the number that minimizes the sum of squared deviations Absolute mean deviation achieves point (1), and absolute median deviation achieves both points (1) and (3). I need to obtain some sort of average among a list of variances, but have trouble coming up with a reasonable solution There is an interesting discussion about the differences among the three
The mean has a proper interpretation outside normal distributions, and it can have problems, such as its vulnerability to outliers (which in some applications is more of a problem than in others) One cannot generally say that the mean should or should not be used if we don't have a normal distribution It depends on what you are interested in. The above calculations also demonstrate that there is no general order between the mean of the means and the overall mean In other words, the hypotheses mean of means is always greater/lesser than or equal to overall mean are also invalid. If you mean of a density plot, then what distribution
Different distributions will have different derivatives at 1 sd from the mean. How would you explain the concept of mean, median, and mode of a list of numbers and why they are important to somebody with only basic arithmetic skills Let's not mention skewness, clt, central
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