Q. In terms of mean absolute deviation, the quartile deviation is equal to

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Q. The price of gasoline for three days are as 98, 96, 97, 100 then the value of standard deviation with the assumed mean method is

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Q. The total order processed at courier office for five days are as 10, 6, 8, 7, 9 then total sum of squares is

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Q. In the formula of sample variance the Σ(x-x̅)² is called

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Q. The mean absolute deviation is 23 and coefficient of mean absolute deviation is 18 then arithmetic mean is

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Q. One of the advantages of using quartile deviation is to use it for

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Q. The letter used to denote variance of population is

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Q. The coefficient of quartile deviation is 10.34% and the difference of first and third quartile is 15 then the sum of third and first quartile is

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Q. If the coefficient of variation is 13.4% and the standard deviation is 12 then the arithmetic mean of that set of observations is

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Q. The difference between first and third quartile is 20 and the sum of first and third quartile is 60 then coefficient of quartile deviation is

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Q. If the first quartile is subtracted from median then the answer must be equal to

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Q. The numbers or values that are considered independent of measurement units are called

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Q. The quartile deviation for number of X-ray patients who visits orthopedic in 7 consecutive days is 14 then mean absolute deviation is

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Q. The measure of variation which is useful in large deviations occurrences on occasional basis is considered as

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Q. The inter quartile range and the coefficients of range are two categories of

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Q. Considering the sample rather than population, the standard deviation is thus denoted by

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Q. According to empirical rule, the standard deviation and mean interval that covers approximately 68.27% of data from a frequency distribution is

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Q. The number of emergency cases in hospital for five days are as 12, 15, 18, 16, 14 then variance of sample is

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Q. The average deviation measures and distance measures are classified as measures of dispersion on the basis of

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Q. In statistics, the distance or dispersion from the central value is classified as

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