Varpa Function

Purpose

Return value

Syntax

=VARPA(number1,[number2],...)

• number1 - First number or reference.
• number2 - [optional] Second number or reference.

Using the VARPA function

The VARPA function calculates the variance for data that represents an entire population. Variance provides a general idea of the spread of data. The difference between the VARPA function and the VARP function is in how these functions handle logical values and numbers as text. The VARP function will ignore text values and logicals when the appear in references , while the VARPA function will evaluate text as zero, TRUE as 1, and FALSE as zero. Note that both VARP and VARPA will evaluate logical values, and numbers as text when they are hardcoded directly as arguments .

Example

In the example shown, the formula in F5 is:

=VARPA(C5:C10)

Note that the VARP function ignores the “NA” text in C8, while VARPA includes this in the variance estimate as zero.

Variation functions in Excel

The table below summarizes the variation functions available in Excel.

Notes

• VARPA assumes data represents the entire population. If data represents a sample, use VARA or VAR.S
• VARPA evaluates text values and logicals in references, unlike VARP.
• Arguments can either be numbers or names, arrays, or references that contain numbers.
• Arguments can be hard-coded values instead of references.
• To ignore logical values and/or text in references, use VARP or VAR.P

Purpose

Return value

Syntax

=WEIBULL(x,alpha,beta,cumulative)

• x - The value at which to evaluate the distribution (must be ≥ 0).
• alpha - The shape parameter of the distribution (must be > 0).
• beta - The scale parameter of the distribution (must be > 0).
• cumulative - A logical value that determines the form of the function. If TRUE, returns the cumulative distribution function; if FALSE, returns the probability density function.

Using the WEIBULL function

The WEIBULL function calculates values for the Weibull distribution, which is a continuous probability distribution commonly used to model the time until failure of a component or system. The Weibull distribution is particularly useful in reliability engineering, survival analysis, and failure time analysis, as it can model increasing, constant, or decreasing failure rates depending on the value of the shape parameter (alpha).

For better accuracy and consistency with other modern statistical functions, it is recommended to use the WEIBULL.DIST function . WEIBULL.DIST uses the same arguments and provides the same core functionality with improved numerical precision. See the WEIBULL.DIST function for more details.

Notes

• WEIBULL is a legacy function. For Excel 2010 and later, use the WEIBULL.DIST function.
• If any argument is non-numeric, WEIBULL returns the #VALUE! error.
• If x < 0, WEIBULL returns the #NUM! error.
• If alpha ≤ 0 or beta ≤ 0, WEIBULL returns the #NUM! error.