Q. If the standard deviation is 7 then mean absolute deviation is

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Q. According to empirical rule, the standard deviation and mean interval that covers approximately 99.75% of data from a frequency distribution is

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Q. The theorem which states least percentage of values that fall within z-standard deviations is classified as

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Q. The categories of measures of dispersion are classified as

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Q. The population variance is also called

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Q. The lesser uniformity of 50% observations around the median value is indicated with the help of

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Q. If the large number of values lies in the central part of data table then the spread of values is measured by

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Q. The formula which considers the relationship between set of observations, standard deviation and mean is classified as

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Q. If the calculated value of total sum of squares in sample variance is larger than the variation in data set is considered as

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Q. The standard deviation of data is 12 and the mean is 72 then coefficient of variation is

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Q. The value of third quartile is 61 and inter quartile range of the set of observation is 48 then value of first quartile is

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Q. If in a formula, the mean absolute deviation is numerator and arithmetic mean is denominator then the resultant value is classified as

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Q. The technique which implies in statistical process to measure the variation in data is called

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Q. If the standard deviation is 5 then quartile deviation is

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Q. The value of third quartile is 72, second quartile is 52 and the first quartile is 45 then quartile deviation is

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Q. The undesirable consequences which causes the estimated population variance to appear less as compared to real results are classified as

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Q. The measuring theorem which helps in determining proportion of observations for specific interval of mean and standard deviation is classified as

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Q. Considering the individual values of data set, the actual mean must always be

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Q. Considering the set of observations, the percentage of values that lies within population mean plus two standard deviations is

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Q. The measure of variation which is useful for highly skewed distribution is

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