WorksheetFunction.Confidence_Norm Method (Excel)
Returns a value that you can use to construct a confidence interval for a population mean.
Version Information
Version Added: Excel 2010
Syntax
expression .Confidence_Norm(Arg1, Arg2, Arg3)
expression A variable that represents a WorksheetFunction object.
Parameters
Name |
Required/Optional |
Data Type |
Description |
|---|---|---|---|
Arg1 |
Required |
Double |
The significance level used to compute the confidence level. The confidence level equals 100*(1 - alpha)%, or in other words, an alpha of 0.05 indicates a 95 percent confidence level. |
Arg2 |
Required |
Double |
The population standard deviation for the data range and is assumed to be known. |
Arg3 |
Required |
Double |
The sample size. |
Return Value
Double
Remarks
The confidence interval is a range of values. Your sample mean, x , is at the center of this range and the range is x ± Confidence_Norm. For example, if x is the sample mean of delivery times for products ordered through the mail, x ± Confidence_Norm is a range of population means. For any population mean, μ 0 , in this range, the probability of obtaining a sample mean further from μ 0 than x is greater than alpha; for any population mean, μ 0 , not in this range, the probability of obtaining a sample mean further from μ 0 than x is less than alpha. In other words, assume that x , standard_dev, and size is used to construct a two-tailed test at significance level alpha of the hypothesis that the population mean is μ 0 . Then we will not reject that hypothesis if μ 0 is in the confidence interval and will reject that hypothesis if μ 0 is not in the confidence interval. The confidence interval does not allow inference that there is probability 1 – alpha that the next package will take a delivery time that is in the confidence interval:
If any argument is nonnumeric, Confidence_Norm generates an error.
If alpha ≤ 0 or alpha ≥ 1, Confidence_Norm generates an error.
If standard_dev ≤ 0, Confidence_Norm generates an error.
If size is not an integer, it is truncated.
If size < 1, Confidence_Norm generates an error.
If it is assumed that alpha equals 0.05, calculate the area under the standard normal curve that equals (1 - alpha), or 95 percent. This value is ± 1.96. The confidence interval is therefore:
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