Nishan Poojary
Shri Madhwa Vadiraja Institute of Technology and Management (SMVITM), Udupi
Nishan Poojary has created this Calculator and 400+ more calculators!
Shashwati Tidke
Vishwakarma Institute of Technology (VIT), Pune
Shashwati Tidke has verified this Calculator and 200+ more calculators!

11 Other formulas that you can solve using the same Inputs

Binomial Probability
Binomial Probability=Combination Probability (nCr)*((Probability of Success)^r Items)*((Probability of Failure )^(n Set-r Items)) GO
Standard deviation of binomial distribution
Standard Deviation=sqrt((Number of trials)*(Probability of Success)*(1-Probability of Success)) GO
Variance of negative binomial distribution.
Variance of distribution=(Number of success*Probability of Failure )/(Probability of Success^2) GO
Standard deviation of negative binomial distribution
Standard Deviation=sqrt((Number of success*Probability of Failure )/(Probability of Success)) GO
Mean of negative binomial distribution
Mean of distribution=(Number of success*Probability of Failure )/Probability of Success GO
Standard deviation of geometric distribution
Standard Deviation=sqrt(Probability of Failure /(Probability of Success^2)) GO
Variance of geometric distribution.
Variance of distribution=Probability of Failure /(Probability of Success^2) GO
variance of binomial distribution
Variance=Number of trials*Probability of Success*(1-Probability of Success) GO
Variance population proportion
Variance=(Probability of Success*Probability of Failure )/Number of trials GO
Mean of geometric distribution
Mean of distribution=Probability of Failure /Probability of Success GO
mean of binomial distribution
Mean of distribution=Probability of Success*Number of trials GO

11 Other formulas that calculate the same Output

Variance of hypergeometric distribution
Variance=((Number of items in sample*Number of success*(Number of items in population-Number of success)*(Number of items in population-Number of items in sample))/((Number of items in population^2)*(Number of items in population-1))) GO
Sample variance
Variance=((sum of difference btw ith term and sample mean^2)/(Number of elements in population-1)) GO
Variance of population
Variance=(sum of difference btw ith term and sample mean^2)/Number of elements in population GO
Variance of population proportion given probability of success
Variance=(Probability of Success*(1-Probability of Success))/Number of trials GO
variance of binomial distribution
Variance=Number of trials*Probability of Success*(1-Probability of Success) GO
Variance population proportion
Variance=(Probability of Success*Probability of Failure )/Number of trials GO
Proportion Of Variance
Variance=1-Residual sum of squares/Total sum of squares GO
Variance
Variance=((Pessimistic time-Optimistic time)/6)^2 GO
Variance Using Z-Score
Variance=((Value of A-Mean of data)/Z-score)^2 GO
Variance Of Data
Variance=(Standard Deviation)^2 GO
Variance of Poisson distribution
Variance=Mean of data GO

variance of proportion Formula

Variance=(Probability of Success*(1-Probability of Success))/(Number of items in population)
σ<sup>2</sup>=(p*(1-p))/(N)
More formulas
Mean of sampling distribution of mean GO
Mean of sampling distribution of proportion GO
Standard deviation of proportion GO
Standard deviation of proportion given probability of success GO
population standard deviation GO
variance of proportion given probability of success GO

What is sampling distribution...?

A sampling distribution is a probability distribution of a statistic obtained from a larger number of samples drawn from a specific population. The sampling distribution of a given population is the distribution of frequencies of a range of different outcomes that could possibly occur for a statistic of a population. A sampling distribution is a statistic that is arrived out through repeated sampling from a larger population. It describes a range of possible outcomes that of a statistic, such as the mean or mode of some variable, as it truly exists a population. The majority of data analyzed by researchers are actually drawn from samples, and not populations.

How to Calculate variance of proportion?

variance of proportion calculator uses Variance=(Probability of Success*(1-Probability of Success))/(Number of items in population) to calculate the Variance, The variance of proportion formula is defined by the formula V = sqrt( P * ( 1 - P ) / n ) where, P is the probability of success n is the population size. Variance and is denoted by σ2 symbol.

How to calculate variance of proportion using this online calculator? To use this online calculator for variance of proportion, enter Probability of Success (p) and Number of items in population (N) and hit the calculate button. Here is how the variance of proportion calculation can be explained with given input values -> 0.001875 = (0.75*(1-0.75))/(100).

FAQ

What is variance of proportion?
The variance of proportion formula is defined by the formula V = sqrt( P * ( 1 - P ) / n ) where, P is the probability of success n is the population size and is represented as σ2=(p*(1-p))/(N) or Variance=(Probability of Success*(1-Probability of Success))/(Number of items in population). Probability of Success is the ratio of success cases over all outcomes and Number of items in population is the count of how many numbers are are there in a population.
How to calculate variance of proportion?
The variance of proportion formula is defined by the formula V = sqrt( P * ( 1 - P ) / n ) where, P is the probability of success n is the population size is calculated using Variance=(Probability of Success*(1-Probability of Success))/(Number of items in population). To calculate variance of proportion, you need Probability of Success (p) and Number of items in population (N). With our tool, you need to enter the respective value for Probability of Success and Number of items in population and hit the calculate button. You can also select the units (if any) for Input(s) and the Output as well.
How many ways are there to calculate Variance?
In this formula, Variance uses Probability of Success and Number of items in population. We can use 11 other way(s) to calculate the same, which is/are as follows -
  • Variance=((Pessimistic time-Optimistic time)/6)^2
  • Variance=(Standard Deviation)^2
  • Variance=1-Residual sum of squares/Total sum of squares
  • Variance=((Value of A-Mean of data)/Z-score)^2
  • Variance=Number of trials*Probability of Success*(1-Probability of Success)
  • Variance=(Probability of Success*Probability of Failure )/Number of trials
  • Variance=((Number of items in sample*Number of success*(Number of items in population-Number of success)*(Number of items in population-Number of items in sample))/((Number of items in population^2)*(Number of items in population-1)))
  • Variance=Mean of data
  • Variance=(Probability of Success*(1-Probability of Success))/Number of trials
  • Variance=(sum of difference btw ith term and sample mean^2)/Number of elements in population
  • Variance=((sum of difference btw ith term and sample mean^2)/(Number of elements in population-1))
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