Q. The degree or extent to which the frequency of the observations in data set are concentrated in given frequency distribution is classified as

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Q. According to notations used by R.A. Fisher, the value of beta one with square root is equivalent to

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Q. The frequency distribution is considered as positively skewed if all the values of distribution moves to

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Q. The percentile and moment system are two groups of

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Q. In kurtosis, the frequency curve which is also classified as normal curve is called

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Q. As compared to measures of variation, the measure of skewness is used to understand concentration of

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Q. In moments, the alphas whose values depends on shape of frequency curve are

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Q. The coefficient of skewness by Karl Pearson, Professor Kelly and professor Bowley are considered as

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Q. If the values of skewness and arithmetic mean is given as 4 and 17 respectively then mode of the values is

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Q. If the median is 12, mean is 15 and the standard deviation of data is 3 then Karl Pearson's coefficient of skewness is

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Q. If all the values move towards one tail of a distribution then this scenario results in

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Q. The moment about mean which is indication of flatness of frequency curve is classified as

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Q. The moment about mean which is considered as measure of dispersion and is equivalent to variance is called

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Q. The first deciles of data is 8, ninth deciles is 12 and fifth deciles is 6 then the coefficient of skewness is

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Q. In statistical procedures, the skewness is used to measure the

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Q. In kurtosis, the frequency curve which looks more peaked than normal curve of bell shaped distribution is classified as

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