Standard Deviation in Sampling Distribution of Proportion Calculator

✖Probability of Success is the probability of a specific outcome occurring in a single trial of a fixed number of independent Bernoulli trials.ⓘ Probability of Success [p]			+10% -10%
✖Sample Size is the total number of individuals present in a particular sample drawn from the given population under investigation.ⓘ Sample Size [n]			+10% -10%

✖Standard Deviation in Normal Distribution is the square root of expectation of the squared deviation of the given normal distribution following data from its population mean or sample mean.ⓘ Standard Deviation in Sampling Distribution of Proportion [σ]

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Standard Deviation in Sampling Distribution of Proportion

Formula

`"σ" = sqrt(("p"*(1-"p"))/"n")`

Example

`"0.060764"=sqrt(("0.6"*(1-"0.6"))/"65")`

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Standard Deviation in Sampling Distribution of Proportion Solution

STEP 0: Pre-Calculation Summary

Formula Used

Standard Deviation in Normal Distribution = sqrt((Probability of Success*(1-Probability of Success))/Sample Size)
σ = sqrt((p*(1-p))/n)
This formula uses 1 Functions, 3 Variables

Functions Used

sqrt - A square root function is a function that takes a non-negative number as an input and returns the square root of the given input number., sqrt(Number)

Variables Used

Standard Deviation in Normal Distribution - Standard Deviation in Normal Distribution is the square root of expectation of the squared deviation of the given normal distribution following data from its population mean or sample mean.
Probability of Success - Probability of Success is the probability of a specific outcome occurring in a single trial of a fixed number of independent Bernoulli trials.
Sample Size - Sample Size is the total number of individuals present in a particular sample drawn from the given population under investigation.

STEP 1: Convert Input(s) to Base Unit

Probability of Success: 0.6 --> No Conversion Required
Sample Size: 65 --> No Conversion Required

STEP 2: Evaluate Formula

Substituting Input Values in Formula

σ = sqrt((p*(1-p))/n) --> sqrt((0.6*(1-0.6))/65)

Evaluating ... ...

σ = 0.06076436202502

STEP 3: Convert Result to Output's Unit

0.06076436202502 --> No Conversion Required

FINAL ANSWER

0.06076436202502 ≈ 0.060764 <-- Standard Deviation in Normal Distribution

(Calculation completed in 00.004 seconds)

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< 5 Sampling Distribution Calculators

Standard Deviation of Population in Sampling Distribution of Proportion

Go Standard Deviation in Normal Distribution = sqrt((Sum of Squares of Individual Values/Population Size)-((Sum of Individual Values/Population Size)^2))

Standard Deviation in Sampling Distribution of Proportion given Probabilities of Success and Failure

Go Standard Deviation in Normal Distribution = sqrt((Probability of Success*Probability of Failure in Binomial Distribution)/Sample Size)

Standard Deviation in Sampling Distribution of Proportion

Go Standard Deviation in Normal Distribution = sqrt((Probability of Success*(1-Probability of Success))/Sample Size)

Variance in Sampling Distribution of Proportion given Probabilities of Success and Failure

Go Variance of Data = (Probability of Success*Probability of Failure in Binomial Distribution)/Sample Size

Variance in Sampling Distribution of Proportion

Go Variance of Data = (Probability of Success*(1-Probability of Success))/Sample Size

Standard Deviation in Sampling Distribution of Proportion Formula

Standard Deviation in Normal Distribution = sqrt((Probability of Success*(1-Probability of Success))/Sample Size)
σ = sqrt((p*(1-p))/n)

What is Sampling Distribution?

The Sampling Distribution is the probability distribution of a statistic calculated from a random sample drawn from a population. It describes how the value of the statistic is likely to vary across different samples of the same size and shape, drawn from the same population. It is an important concept in statistics because it allows us to make inferences about a population based on sample data. For example, by understanding the sampling distribution of the mean, we can estimate the mean of a population based on the mean of a sample, and calculate the probability that the estimate is close to the true population mean.

How to Calculate Standard Deviation in Sampling Distribution of Proportion?

Standard Deviation in Sampling Distribution of Proportion calculator uses Standard Deviation in Normal Distribution = sqrt((Probability of Success*(1-Probability of Success))/Sample Size) to calculate the Standard Deviation in Normal Distribution, Standard Deviation in Sampling Distribution of Proportion formula is defined as the square root of expectation of the squared deviation of the random variable that follows sampling distribution of proportion, from its mean. Standard Deviation in Normal Distribution is denoted by σ symbol.

How to calculate Standard Deviation in Sampling Distribution of Proportion using this online calculator? To use this online calculator for Standard Deviation in Sampling Distribution of Proportion, enter Probability of Success (p) & Sample Size (n) and hit the calculate button. Here is how the Standard Deviation in Sampling Distribution of Proportion calculation can be explained with given input values -> 0.060764 = sqrt((0.6*(1-0.6))/65).

FAQ

What is Standard Deviation in Sampling Distribution of Proportion?

Standard Deviation in Sampling Distribution of Proportion formula is defined as the square root of expectation of the squared deviation of the random variable that follows sampling distribution of proportion, from its mean and is represented as σ = sqrt((p*(1-p))/n) or Standard Deviation in Normal Distribution = sqrt((Probability of Success*(1-Probability of Success))/Sample Size). Probability of Success is the probability of a specific outcome occurring in a single trial of a fixed number of independent Bernoulli trials & Sample Size is the total number of individuals present in a particular sample drawn from the given population under investigation.

How to calculate Standard Deviation in Sampling Distribution of Proportion?

Standard Deviation in Sampling Distribution of Proportion formula is defined as the square root of expectation of the squared deviation of the random variable that follows sampling distribution of proportion, from its mean is calculated using Standard Deviation in Normal Distribution = sqrt((Probability of Success*(1-Probability of Success))/Sample Size). To calculate Standard Deviation in Sampling Distribution of Proportion, you need Probability of Success (p) & Sample Size (n). With our tool, you need to enter the respective value for Probability of Success & Sample Size 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 Standard Deviation in Normal Distribution?

In this formula, Standard Deviation in Normal Distribution uses Probability of Success & Sample Size. We can use 2 other way(s) to calculate the same, which is/are as follows -

Standard Deviation in Normal Distribution = sqrt((Probability of Success*Probability of Failure in Binomial Distribution)/Sample Size)
Standard Deviation in Normal Distribution = sqrt((Sum of Squares of Individual Values/Population Size)-((Sum of Individual Values/Population Size)^2))

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