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Q: Which of the following is least affected if an extreme high outlier is added to your data mean median or standard deviation or ALL?

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When you are looking for a simple measure of the spread of the data, but one which is protected from the effects of extreme values (outliers).

It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.

The mean is most affected. Mode and Median are not influenced as much by outliers.

Of the mean, median and mode the mean would be most affected.

Merits· It can be easily calculated and simply understood.· It does not involve much mathematical difficulties.· As it takes middle 50% terms hence it is a measure better than Range and percentile Range.· It is not affected by extreme terms as 25% of upper and 25% of lower terms are left out.· Quartile Deviation also provides a short cut method to calculate Standard Deviation using the formula 6 Q.D. = 5 M.D. = 4 S.D.· In case we are to deal with the centre half of a series this is the best measure to use.Demerits or Limitations· As Q1 and Q3 are both positional measures hence are not capable of further algebraic treatment.· Calculation are much more, but the result obtained is not of much importance.· It is too much affected by fluctuations of samples.· 50% terms play no role; first and last 25% items ignored may not give reliable result.· If the values are irregular, then result is affected badly.· We can't call it a measure of dispersion as it does not show the scatter-ness around any average.· The value of quartile may be same for two or more series or Q.D. is not affected by the distribution of terms between Q1 and Q3 or outside these positions.So going through the merits and demerits, we conclude that Quartile Deviation cannot be relied on blindly. In the case of distributions with high degree of variation, quartile deviation has less reliability.

Related questions

extreme lack of attention to medical care

Generally not without further reason. Extreme values are often called outliers. Eliminating unusually high values will lower the standard deviation. You may want to calculate standard deviations with and without the extreme values to identify their impact on calculations. See related link for additional discussion.

Submarines are not affected by extreme weather.

The reason the standard deviation of a distribution of means is smaller than the standard deviation of the population from which it was derived is actually quite logical. Keep in mind that standard deviation is the square root of variance. Variance is quite simply an expression of the variation among values in the population. Each of the means within the distribution of means is comprised of a sample of values taken randomly from the population. While it is possible for a random sample of multiple values to have come from one extreme or the other of the population distribution, it is unlikely. Generally, each sample will consist of some values on the lower end of the distribution, some from the higher end, and most from near the middle. In most cases, the values (both extremes and middle values) within each sample will balance out and average out to somewhere toward the middle of the population distribution. So the mean of each sample is likely to be close to the mean of the population and unlikely to be extreme in either direction. Because the majority of the means in a distribution of means will fall closer to the population mean than many of the individual values in the population, there is less variation among the distribution of means than among individual values in the population from which it was derived. Because there is less variation, the variance is lower, and thus, the square root of the variance - the standard deviation of the distribution of means - is less than the standard deviation of the population from which it was derived.

no

Generally MICROWAVE based Line of Sight transmissions are adversely affected by extreme weathe conditions.

When you are looking for a simple measure of the spread of the data, but one which is protected from the effects of extreme values (outliers).

It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.

the variance

nothing

Because the standard deviation is based on the square root of the sum of the squares of the deviations, and, as a result, the sum of the squares of the deviations puts more weight in outliers than does a simple arithmetic mean.Note: I wrote this and then had second thoughts, but I'm keeping it in so that someone with more knowledge can weigh in (pun intended). I'm not certain how the arithmetic mean factors into the question. I think the questioner, and definitely this answerer, is confused.

extreme heat and pressure

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