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In two dimensional Euclidean space straight lines are either parallel or convergent. If they are parallel, the perpendicular distance between them is constant and if they are convergent, the distance between them increases in one direction and decreases in the other - until they intersect - and then increases.

In 3-dimensional space, there is a third possibility. You can have lines that are neither parallel nor convergent: they are skew. It is simplest to explain with an example.

Imagine you are standing in a cuboid room, facing a wall. Now consider the principal diagonal, running from the left-bottom-back to the right-top-front, and the line where the wall opposite meets the floor. These too lines will never meet but they are not parallel either.

Q: What is skewness between two lines?

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distinguish between dispersion and skewness

Negative skewness means the average (mean) will be less than the median. Positive skewness means the opposite. I'm not sure if any rule holds for the mode.

the use of the pearson's of skewness

if coefficient of skewness is zero then distribution is symmetric or zero skewed.

Parallell * * * * * It is the angle between the two lines.

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distinguish between dispersion and skewness

Answer this question...similarities and differences between normal curve and skewness

Negative skewness means the average (mean) will be less than the median. Positive skewness means the opposite. I'm not sure if any rule holds for the mode.

the use of the pearson's of skewness

if coefficient of skewness is zero then distribution is symmetric or zero skewed.

You make comparisons between their mean or median, their spread - as measured bu the inter-quartile range or standard deviation, their skewness, the underlying distributions.

No. Skewness is 0, but kurtosis is -3, not 3.No. Skewness is 0, but kurtosis is -3, not 3.No. Skewness is 0, but kurtosis is -3, not 3.No. Skewness is 0, but kurtosis is -3, not 3.

Parallell * * * * * It is the angle between the two lines.

No Man's Land is the name of the space between the two sides front lines.

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.

two

skewness=(mean-mode)/standard deviation