Compatibility
Excel 2007 (Compatibility)
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=VARP()
Calculates variance based on the entire population.
Applies To:
Excel for Microsoft 365Excel for Microsoft 365 for MacExcel 2024Excel 2024 for MacExcel 2021Excel 2021 for MacExcel 2019Excel 2016
=VARP(number1,[number2],...)
Hover argument names in the table for details.
Output typeNumber
Popularity23 / 100
VolatileNo
Dynamic ArrayNo
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◧ Arguments
| Argument | Type | Required | Description |
|---|---|---|---|
number1 |
Number/Range | Required | The first number argument corresponding to a population. |
number2 |
Number/Range | Optional | ,... Optional. Number arguments 2 to 255 corresponding to a population. |
▣ Examples
واریانس استحکام شکست برای تمام ابزارها، با فرض اینکه فقط ۱۰ ابزار تولید شدهاند (کل جامعه)
=VARP(A2:A11)
این مثال از تابع VAR که فرض میکند فقط نمونهای از جامعه است استفاده میکند و نتیجه متفاوتی برمیگرداند
=VAR(A2:A11)
✦ Tips
- This function has been replaced with one or more new functions that may provide improved accuracy and whose names better reflect their usage. Although this function is still available for backward compatibility, you should consider using the new functions from now on, because this function may not be available in future versions of Excel.
- VARP assumes that its arguments are the entire population. If your data represents a sample of the population, then compute the variance by using VAR.
- Arguments can either be numbers or names, arrays, or references that contain numbers.
- Logical values, and text representations of numbers that you type directly into the list of arguments are counted.
- If an argument is an array or reference, only numbers in that array or reference are counted. Empty cells, logical values, text, or error values in the array or reference are ignored.
- Arguments that are error values or text that cannot be translated into numbers cause errors.
- If you want to include logical values and text representations of numbers in a reference as part of the calculation, use the VARPA function.
- The equation for VARP is: where x is the sample mean AVERAGE(number1,number2,…) and n is the sample size.
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