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.
There is no meaningful average wen data are categorical (qualitative). Also, the arithmetic mean is not a good measure of central tendency when the data distribution is skewed.
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.
A normal distribution is not skewed. Skewness is a measure of how the distribution has been pulled away from the normal.A feature of a distribution is the extent to which it is symmetric.A perfectly normal curve is symmetric - both sides of the distribution would exactly correspond if the figure was folded across its median point.It is said to be skewed if the distribution is lop-sided.The word, skew, comes from derivations associated with avoiding, running away, turning away from the norm.So skewed to the right, or positively skewed, can be thought of as grabbing the positive end of the bell curve and dragging it to the right, or positive, direction to give it a long tail in the positive direction, with most of the data still concentrated on the left.Then skewed to the left, or negatively skewed, can be thought of as grabbing the negative end of the bell curve and dragging it to the left, or negative, direction to give it a long tail in the negative direction, with most of the data still bunched together on the right.Warning: A number of textbooks are not correct in their use of the term 'skew' in relation to skewed distributions, especially when describing 'skewed to the right' or 'skewed to the left'.
True
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.
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.
positively skewed
on the left and when it is skewed left it is on the right
See related links.
skewed
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
If it is very highly skewed then the mode is best.
When a set of votes has been skewed it means that either the mean is higher than the median or lower. If it is higher the vote is said to be skewed to the right and when lower it is skewed to the left.
As the mean is greater than the median it will be positively skewed (skewed to the right), and if the median is larger than the mean it will be negatively skewed (skewed to the left)
When the data 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