# How to use the CONFIDENCE function

**What is the CONFIDENCE function?**

The CONFIDENCE function calculates the confidence interval for a population mean, using a normal distribution.

There are newer better functions that may have improved accuracy, this function is available for compatibility with older workbooks created in earlier Excel versions and other older software.

The new CONFIDENCE.NORM function and the CONFIDENCE.T function replace the older CONFIDENCE function which have better accuracy and improved functionality, Microsoft informs that the CONFIDENCE function may not be available in future Excel versions and recommends using the CONFIDENCE.NORM or the CONFIDENCE.T from now on.

**What is a confidence interval?**

A confidence interval is a range of values used to estimate a population parameter based on a sample statistic. It is constructed using a point estimate (such as the sample mean) plus or minus a margin of error.

The confidence level indicates the probability that the true population parameter lies within the interval. 90%, 95% and 99% confidence levels are commonly used.Â Useful for quantifying the uncertainty and potential error in statistics, surveys, polls, etc.

**What is a population sample?**

A population sample in statistics refers to a subset of data points selected from a larger population.Â The sample is a portion drawn from the total population.

It is studied to make inferences about the whole population, a sample aims to represent the population characteristics. The sample should be chosen randomly when possible to avoid bias.

The sample size should be adequate to represent the population, larger samples produce more precise results. Sampling reduces the cost and effort of studying the entire population and results are subject to sampling error due to studying a subset only.

**How to pick a sample size to represent the population?**

A typical starting point is to sample 5-10% of a large population or 20-30% of a small population. Statistical equations using confidence level, margin of error, and variance can precisely calculate the optimal sample size.

The goal is to pick a sample size large enough to produce a reasonable margin of error and desired power at a given confidence level. Higher confidence in the results requires a larger sample. Common levels are 90%, 95%, 99%.

The amount of potential error tolerated in results. Lower margin needs a larger sample. Larger populations require a bigger sample. Smaller populations need a higher sampling percentage. Bigger samples require more time, money and effort. Need to balance accuracy and feasibility.

**What is a population mean?**

The population mean is the average value of a quantitative variable calculated across an entire population also called the expected value or population average.

It is calculated by summing all the values in the population and dividing by the total number of individuals and is represented by the Greek letter Î¼ (mu).

**What is a normal distribution?**

The normal distribution is a symmetric bell-shaped probability distribution described by its mean and standard deviation. Used by many to model a plethora of natural phenomena and represent unknown processes.

## CONFIDENCE Function Syntax

CONFIDENCE(*alpha*, *standard_dev*, *size*)

## CONFIDENCE Function Arguments

alpha |
Required. The significance level used to calculate the confidence level. 0.05 represents a 95% confidence level. |

standard_dev |
Required. The standard deviation for the data points. |

size |
Required. The number of data points. |

## CONFIDENCE Function Example

Formula in cell B6:

## CONFIDENCE Function not working

The CONFIDENCE function returns an

- #VALUE! error if an argument is not a number.
- #NUM! if alpha is less than 0 (zero) or more than 1.

### Functions in 'Compatibility' category

The CONFIDENCE function is one of 21 functions in the 'Compatibility' category.

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