181.
The variance of 19, 21, 23, 25 and 27 is 8. The variance of 14, 16, 18, 20 and 22 is:
A
Greater than 8
B
8
C
Less than 8
D
8 - 5 = 3
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The variance of 19, 21, 23, 25 and 27 is 8. The variance of 14, 16, 18, 20 and 22 is:
Greater than 8
8
Less than 8
8 - 5 = 3
The mean of an examination is 69, the median is 68, the mode is 67, and the standard deviation is 3. The measures of variation for this examination is:
67
68
69
3
Standard deviation is always calculated from:
Mean
Median
Mode
Lower quartile
To compare the variation of two or more than two series, we use
Combined standard deviation
Corrected standard deviation
Coefficient of variation
Coefficient of skewness
If Var(X) = 25, then is equal to:
15-Feb
50
25
5
Which of the following statements is false?
The standard deviation is independent of change of origin
If the moment coefficient of kurtosis β2 = 3, the distribution is mesokurtic or normal.
If the frequency curve has the same shape on both sides of the centre line which divides the curve into two equal parts, is called a symmetrical distribution.
Variance of the sum or difference of any two variables is equal to the sum of their respective variances
Which of the following statements is correct?
The standard deviation of a constant is equal to unity
The sum of absolute deviations is minimum if these deviations are taken from the mean.
The second moment about origin equals variance
The variance is positive quantity and is expressed in square of the units of the observations
The ratio of the standard deviation to the arithmetic mean expressed as a percentage is called:
Coefficient of standard deviation
Coefficient of skewness
Coefficient of kurtosis
Coefficient of variation
If Y = aX + b, where a and b are any two numbers but a ≠ 0, then S.D(Y) is equal to:
S.D(X)
a S.D(X)
|a| S.D(X)
a S.D(X) + b
If Y = aX ± b, where a and b are any two constants and a ≠ 0, then Vat (Y) is equal to:
a Var(X)
a Var(X) + b
a2 Var(X) – b
a2 Var(X)
For two independent variables X and Y if S.D(X) = 1 and S.D(Y) = 3, then Var(3X - Y) is equal to:
18
12
6
S.D(X) = 6 and S.D(Y) = 8. If X and Yare independent random variables, then S.D(X-Y) is:
10
14
100
2
The standard deviation is independent of:
Change of scale of measurement
Change of origin and scale of measurement
Difficult to tell
Change of origin
The variance is zero only if all observations are the:
Square
Square root
Same
Different
The positive square root of the mean of the squares of the cleviations of observations from their mean is called:
Range
Standard deviation
Coefficient of variation
Variance
The standard deviation one distribution dividedly the mean of the distribution and expressing in percentage is called:
Coefficient of skewness
Coefficient of quartile deviation
Coefficient of variation
Coefficient of Standard deviation
The value of standard deviation changes by a change of:
Scale
Algebraic signs
None
Origin
If the dispersion is small, the standard deviation is:
Zero
Small
Negative
Large
Which of the following is a unit free quantity:
Standard deviation
Coefficient of variation
Arithmetic mean
Range
Which measure of dispersion has a different unit other than the unit of measurement of values:
Standard deviation
Variance
Mean deviation
Range