MORE INFORMATION
NORMSINV(p) returns the value z such that, with probability
p, a standard normal random variable takes on a value that is less than or
equal to z. A standard normal random variable has mean 0 and standard deviation
1 (and also variance 1 because variance = standard deviation squared).
Syntax
NORMSINV(p)
where p is a numeric value. Because p corresponds to a probability, it
must be greater than 0 and less than 1.
Example Usage
NORMSINV and NORMSDIST are related functions. If NORMSDIST(z)
returns p, then NORMSINV(p) returns z.
Create a blank Excel worksheet,
copy the table below, select cell A1 in your blank Excel worksheet, and then
click
Paste on the
Edit menu so that the
entries in the table below fill cells A1:C24 in your worksheet.
z | NORMSDIST(z) | NORMSINV(NORMSDIST(z)) |
| | |
0 | =NORMSDIST(A3) | =NORMSINV(B3) |
0.2 | =NORMSDIST(A4) | =NORMSINV(B4) |
0.4 | =NORMSDIST(A5) | =NORMSINV(B5) |
0.6 | =NORMSDIST(A6) | =NORMSINV(B6) |
0.8 | =NORMSDIST(A7) | =NORMSINV(B7) |
1 | =NORMSDIST(A8) | =NORMSINV(B8) |
1.5 | =NORMSDIST(A9) | =NORMSINV(B9) |
2 | =NORMSDIST(A10) | =NORMSINV(B10) |
2.5 | =NORMSDIST(A11) | =NORMSINV(B11) |
| | |
p | NORMSINV(p) | |
0.5 | =NORMSINV(A14) | |
0.6 | =NORMSINV(A15) | |
0.9 | =NORMSINV(A16) | |
0.95 | =NORMSINV(A17) | |
0.975 | =NORMSINV(A18) | correct NORMSINV(p) |
0.001 | =NORMSINV(A19) | -3.09023 |
0.0001 | =NORMSINV(A20) | -3.71902 |
0.00001 | =NORMSINV(A21) | -4.26489 |
0.000001 | =NORMSINV(A22) | -4.75342 |
0.0000003 | =NORMSINV(A23) | -4.99122 |
0.0000002 | =NORMSINV(A24) | -5.06896 |
Note After you paste this table into your new Excel worksheet, click
the
Paste Options button, and then click
Match
Destination Formatting. With the pasted range still selected, point to
Column on the
Format menu, and then click
AutoFit Selection. You may want to format columns B and C for
consistent readability (such as Numbers with 5 decimal places).
Cells
A1:B11 give a "mini-Normal table" similar to what you might have seen in a
statistics text except that such tables contain rows for many values of z
between those in A2:A11 and higher than the value 2.5 in A11.
Cells
A13:B24 illustrate the use of NORMSINV. Because 0.5 in cell A14 appears in cell
B3, it follows that the appropriate z value that yields NORMSDIST = 0.5 is 0
and NORMSINV(0.5) returns 0. In cell B15, you want that value of z where
NORMSDIST(z) = 0.6. Entries in A4:B5 indicate that the appropriate value of z
must be between 0.2 and 0.4. It must be greater than 0.2 because NORMSDIST(0.2)
is less than 0.6 and it must be less than 0.4 because NORMSDIST(0.4) is greater
than 0.6. The computation of NORMSINV in B15 yields the value 0.25335, this is
indeed greater than 0.2 and less than 0.4. Analogously, NORMSINV(0.9) in B16
must be greater than 1 and less than 1.5 as revealed by entries in A8:B9; and
the answer, 1.28155, is indeed within this range. Also, NORMSINV(0.95) in B17
must be greater than 1.5 and less than 2.0 as revealed by entries in A9:B10;
and the answer, 1.644485, is within this range. Finally, NORMSINV(0.975) must
also be between 1 and 1.5 according to A10:B11. Because .975 is much closer to
.977 than to .933, you expect NORMSINV(0.975) to be much closer to 2 than to
1.5; and it is at 1.965996.
As an aside, past users of statistical
tables for statistical hypothesis testing and computation of confidence
intervals might recognize the values in A17:B18. Probability 0.05 lies in the
right tail above 1.644485 because NORMSDIST(1.644485) = .95 and probability
0.025 lies in the right tail above 1.965996 because NORMSDIST(1.965996) = .975.
These cutoff values are frequently used for one-tailed and two-tailed
hypothesis tests respectively when the probability of rejecting the null
hypothesis if true is set at 0.05.
Values in C3:C11 verify the
reciprocal relationship between a function and its inverse, in this case
between NORMSDIST and NORMSINV. It should be the case that z =
NORMSINV(NORMSDIST(z)). If you re-format these entries to show many more
decimal places, you might notice that the result is not exact because of
imprecision of NORMSDIST, NORMSINV or both. However, errors appear only after a
large enough number of decimal places that they are unlikely to be of concern
to a user. Results in Excel 2003 will be improved over those in Excel 2002 and
results in Excel 2002 will be improved over earlier versions.
A19:C24
show values of NORMSINV(p) for your current version of Excel for increasingly
smaller values of p. Entries in column C are taken from Table 5 in Knusel, L.
On the Accuracy of Statistical
Distributions in Microsoft Excel 97, Computational Statistics and Data Analysis, 26, 375-377, 1998.
Results in Earlier Versions of Excel
The accuracy of the NORMSINV function depends on two factors.
Because the calculation of the NORMSINV function uses a systematic search over
the returned values of the NORMSDIST function, the accuracy of the NORMSDIST
function is critical.
Also, the search must be sufficiently refined
that it "homes in" on an appropriate answer. To use the textbook Normal
probability distribution table as an analogy, entries in the table must be
accurate. Also, the table must contain so many entries that you can find the
appropriate row of the table that yields a probability that is correct to a
specific number of decimal places.
Of course, by using a computer
program, you do not have to build and store such a large table. Instead,
individual entries are computed on demand as the search through the "table"
proceeds. However, the table must be accurate and the search must continue far
enough that it does not stop prematurely at an answer that has a corresponding
probability (or row of the table) that is too far from the value of
p that you use in the call to
NORMSINV(
p). Therefore, the NORMSINV function has
been improved in the following ways:
- The accuracy of the NORMSDIST function has been
improved.
- The search process has been improved to increase
refinement.
The NORMSDIST function has been improved in Excel 2003. Improved
refinements in the search process were introduced in Microsoft Excel 2002. An
article by Knusel (see note 2) discusses numeric deficiencies in the NORMSINV
function in Microsoft Excel 97. These deficiencies persisted as documented by
Knusel until the improvements in the search process in Excel 2002 made results
better, but still not in complete agreement with Knusel's.
Note 2 Knusel, L.
On the Accuracy of Statistical Distributions in
Microsoft Excel 97, Computational Statistics and Data Analysis, 26, 375-377, 1998.
Results in Excel 2003
The procedure for calculating the NORMSINV function in Excel 2003
takes advantage of improvements in the NORMSDIST function in Excel
2003.
For additional
information, click the following article number to view the article in the
Microsoft Knowledge Base:
827369
Excel Statistical Functions: NORMSDIST
Results should always agree with Knusel's to the
number of decimal places shown.
Conclusions
Typically, inaccuracies in earlier versions of Excel occur for
extremely small or extremely large values of
p in
NORMSINV(
p). The values in Excel 2003 are much more
accurate.
The article about the NORMSDIST function mentions that most
users are not likely to be affected by the inaccuracies in the NORMSDIST
function that appear in earlier versions of Excel. Therefore, users of Excel
2002 are not likely to be affected by inaccuracies in the NORMSINV function
because the search process refinements were added to Excel 2002. However, for
users of earlier versions of Excel (before Excel 2002), there is more concern
about the inaccuracy of the NORMSINV function because both the NORMSDIST
function and the search process needed improvement in those earlier
versions.
For more information
about NORMSINV, click
Microsoft Office Excel Help on the
Help menu, type
normsinv in the
Search for box in the Assistance pane, and then click
Start searching to view the topic.