Here is a sample formula to calculate the sample variance of a variable X with n observations:

Var(X) = ∑(X - X̄)^2 / (n-1)

Where X̄ is the sample mean, X is an individual observation in the sample, ∑(X - X̄)^2 is the sum of the squared differences between each observation and the sample mean, and n is the sample size.

Here's an example:

Suppose you have a sample of 5 observations of a variable X: [1, 2, 3, 4, 5].

The sample mean is (1 + 2 + 3 + 4 + 5) / 5 = 15 / 5 = 3.

The variance can be calculated as follows:

Var(X) = ( (1-3)^2 + (2-3)^2 + (3-3)^2 + (4-3)^2 + (5-3)^2 ) / (5-1)
= ( 4 + 1 + 0 + 1 + 4 ) / 4
= 10 / 4
= 2.5

So the variance of the variable X in this sample is 2.5.
Here is a sample formula to calculate the sample variance of a variable X with n observations:

Var(X) = ∑(X - X̄)^2 / (n-1)

Where X̄ is the sample mean, X is an individual observation in the sample, ∑(X - X̄)^2 is the sum of the squared differences between each observation and the sample mean, and n is the sample size.

Here's an example:

Suppose you have a sample of 5 observations of a variable X: [1, 2, 3, 4, 5].

The sample mean is (1 + 2 + 3 + 4 + 5) / 5 = 15 / 5 = 3.

The variance can be calculated as follows:

Var(X) = ( (1-3)^2 + (2-3)^2 + (3-3)^2 + (4-3)^2 + (5-3)^2 ) / (5-1)
= ( 4 + 1 + 0 + 1 + 4 ) / 4
= 10 / 4
= 2.5

So the variance of the variable X in this sample is 2.5.
user
I hope that helps! Let me know if you have any other questions.

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assistant
Here is a sample formula to calculate the sample variance of a variable X with n observations:

Var(X) = ∑(X - X̄)^2 / (n-1)

Where X̄ is the sample mean, X is an individual observation in the sample, ∑(X - X̄)^2 is the sum of the squared differences between each observation and the sample mean, and n is the sample size.

Here's an example:

Suppose you have a sample of 5 observations of a variable X: [1, 2, 3, 4, 5].

The sample mean is (1 + 2 + 3 + 4 + 5) / 5 = 15 / 5 = 3.

The variance can be calculated as follows:

Var(X) = ( (1-3)^2 + (2-3)^2 + (3-3)^2 + (4-3)^2 + (5-3)^2 ) / (5-1)
= ( 4 + 1 + 0 + 1 + 4 ) / 4
= 10 / 4
= 2.5

So the variance of the variable X in this sample is 2.5.
user
It's important to note that the variance is a measure of the dispersion or spread of the data around the mean. A larger variance indicates that the data is more spread out, while a smaller variance indicates that the data is more clustered around the mean.

In addition, the variance is often used as a measure of the uncertainty or variability of a sample statistic, such as the sample mean. In this case, the variance is often divided by the sample size to obtain the sample standard deviation, which is a measure of the average distance of the data from the mean.
assistant
Here is a sample formula to calculate the sample variance of a variable X with n observations:

Var(X) = ∑(X - X̄)^2 / (n-1)

Where X̄ is the sample mean, X is an individual observation in the sample, ∑(X - X̄)^2 is the sum of the squared differences between each observation and the sample mean, and n is the sample size.

Here's an example:

Suppose you have a sample of 5 observations of a variable X: [1, 2, 3, 4, 5].

The sample mean is (1 + 2 + 3 + 4 + 5) / 5 = 15 / 5 = 3.

The variance can be calculated as follows:

Var(X) = ( (1-3)^2 + (2-3)^2 + (3-3)^2 + (4-3)^2 + (5-3)^2 ) / (5-1)
= ( 4 + 1 + 0 + 1 + 4 ) / 4
= 10 / 4
= 2.5

So the variance of the variable X in this sample is 2.5.
user
I hope that helps! Let me know if you have any other questions.

## We’ll help your grades soar

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## Popular Summaries

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## 24/7 Support

Get help, not hassle. Our world-class customer support team is always available when you need it.
assistant