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Q: Should you use the median or mean to describe a data set if the data are not skewed?

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If the skewness is different, then the data sets are different.Incidentally, there is one [largely obsolete] definition of skewness which is in terms of the mean and median. Under that definition, it would be impossible for two data sets to have equal means and equal medians but opposite skewness.

Skewing in mathematics deals with statistics and with the averages of a given set of numbers. When talking about skewing, the group of numbers is usually skewed to the left, meaning most of the data falls below the median, or to the right, making most of the data above the median. Skewing can be caused by pieces of the data being very high above or below the rest of the data.

There isn't a specific chart for skewed data, but you could use a number of different charts to show that data is skewed. An Area chart could be used for example, or a column chart could also work. It would depend in the nature of the data.

They all describe data set or data sets,hey tell you how far apart they are from each other.

MEDIANUse the median to describe the middle of a set of data that does have an outlier.Advantages:• Extreme values (outliers) do not affect the median as strongly as they do the mean.• Useful when comparing sets of data.• It is unique - there is only one answer.Disadvantages:• Not as popular as mean.

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The population data may be skewed and thus the mean is not a valid statistic. If mean > median, the data will be skewed to the right. If median > mean, the data is skewed to the left.

You would use the median if the data were very skewed, with extreme values.

i) Since Mean<Median the distribution is negatively skewed ii) Since Mean>Median the distribution is positively skewed iii) Median>Mode the distribution is positively skewed iv) Median<Mode the distribution is negatively skewed

Measurement Scale Best measure of the 'middle' Numerical mode Ordinal Median Interval Symmetrical data- mean skewed data median Ratio Symmetrical data- Mean skewed data median

The mean is used for evenly spread data, and median for skewed data. Not sure when the mode should be used.

When the data distribution is negatively skewed.

Either can be used for symmetrical distributions. For skewed data, the median may be more a appropriate measure of the central tendency - the "average".

If the median is exactly in the middle of the box, and the box is exactly in the middle of the whiskers, then skewness = 0. The data are skewed if either the median is off-centre in the box, or if the box is off-centre overall.

A positively skewed or right skewed distribution means that the mean of the data falls to the right of the median. Picturewise, most of the frequency would occur to the left of the graph.

Yes. Central tendency is the way data clusters around a value. Even if the distribution of the value is skewed, the median would be the best indicator of central tendency because of the way the data is clustered.

The answer depends on the type of data. The mean or median are useless if the data are qualitative (categoric): only the mode is any use. The median is better than the mean is the data are very skewed.

Can the median and mode be used to describe both categorical data and numerical data