Best Answer

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

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Q: When is data negatively or positively skewed?

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Not necessarily.

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)

No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.

positively skewed

It is a positively skewed distribution.

Related questions

Not necessarily.

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.

When the data distribution is negatively skewed.

If most the population has many high scores, the distribution is negatively skewed. If most have many low scores, it is positively skewed

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)

No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.

positively 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.

It is a positively skewed distribution.

One of the characteristics of mean when measuring central tendency is that when there are positively skewed distributions, the mean is always greater than the median. Another characteristic is that when there are negatively skewed distributions, the mean is always less than the median.

negatively

negatively

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