A simple random sample of 100 observations was taken from a large population. The sample mean and the standard deviation was determined to be 80 and 12, respectively. The standard error of mean is _______
Concept:
No of observations
\(N = {\left( {\frac{{{C_V}}}{ϵ}} \right)^2}\)
Where,
ϵ = allowable % error of mean
Cv = coefficient of variation.
\(C_v= \frac{\sigma}{\bar{x}}~\times 100\)
σ = Standard deviation, x̅ = Mean
Calculation:
Given:
x̅ = 80, σ = 12, N = 100
\(C_v= \frac{\sigma}{\bar{x}}~\times 100\)
\({C_v} = \frac{{12}}{{80}} × 100\)
Cv = 15%
\(N = {\left( {\frac{{{C_V}}}{ϵ}} \right)^2}\)
\(100 = {\left( {\frac{{{15}}}{ϵ}} \right)^2}\)
ϵ = 1.5%
The standard error of mean = mean × percentage of absolute mean error = \(80\times {{1.5} \over 100}\) = 1.2
Important Questions from Statistical Variables
Which of these statements on variation is INCORRECT?
For a group of 5 male residents in a society, the mean and standard deviation of their ages are 63 years and 9 years, respectively. For a group of 4 female residents, these values are 54 years and 6 years, respectively. The variance of the combined group of male and female residents is:
Factory A and Factory B employ 476 and 524 employees. respectively. The average weekly salary of an employee in Factory A is $34.5 whereas for an employee in Factory B it is $28.5, The standard deviation in paying the individual salary has been recorded as $5 and $4.5 for Factory A and Factory B, respectively. Which factory has greater variability in paying individual salary?
Among the options for parameters, which option is correct for population?
The formula to calculate the coefficient of quartile deviation is
