COEFFICIENT OF VARIATION CONFIDENCE LIMITS

COEFFICIENT OF VARIATION CONFIDENCE LIMITS

Analysis Command

Generates a confidence interval for the coefficient of variation for normally distributed data.

The coefficient of variation is defined as the ratio of the standard deviation to the mean
\( \mbox{cv} = \frac{\sigma} {\mu} \)

where \( \sigma \) and \( \mu \) denote the population standard deviation and population mean, respectively. The sample coefficient of variation is defined as

\( \hat{\mbox{cv}} = \frac{s} {\bar{x}} \)

where s and \( \bar{x} \) denote the sample standard deviation and sample mean respectively.

The coefficient of variation should typically only be used for ratio data. That is, the data should be continuous and have a meaningful zero. Although the coefficient of variation statistic can be computed for data that is not on a ratio scale, the interpretation of the coeffcient of variation may not be meaningful. Currently, this command is only supported for non-negative data. If the response variable contains one or more negative numbers, an error message will be returned.

For normally distributed data, a number of methods for determining confidence intervals for the coefficient of variation have been proposed. Dataplot currently supports six different methods.

In the following, \( \bar{x} \), s, n, and K denote the sample mean, sample standard deviation, sample size, and sample coefficient of variation, respectively. CHSPPF denotes the chi-square percent point function and \( \alpha \) denotes the significance level.

The supported methods are

1. The "naive" method is based on dividing the standard confidence limit for the standard deviation by the sample mean.

   \[ \mbox{lcl} = \frac{s}{\bar{x}} \sqrt{\frac{n-1}{\chi^{2}_{(1-\alpha/2;n-1)}}} \]

   \[ \mbox{ucl} = \frac{s}{\bar{x}} \sqrt{\frac{n-1}{\chi^{2}_{(\alpha/2;n-1)}}} \]

   This method is generally not as accurate as the McKay and modified McKay methods. However, it is sometimes used in practice.

   This method can be specified with the command

   SET COEFFICIENT OF VARIATION CONFIDENCE LIMIT METHOD ...             NAIVE

2. The McKay confidence limit is

   \[ \mbox{lcl} = \frac{K} {\sqrt{\left( \frac{u_1}{n} - 1 \right) K^2 + \frac{u_1}{n-1}}} \]

   \[ \mbox{ucl} = \frac{K} {\sqrt{\left( \frac{u_2}{n} - 1 \right) K^2 + \frac{u_2}{n-1}}} \]

   where

   \[ u_1 = \chi^2_{1 - \alpha/2,n-1} \]

   \[ u_2 = \chi^2_{\alpha/2,n-1} \]

   McKay's approximation is asymptotically exact as n goes to infinity. McKay recommends this approximation only if the coefficient of variation is less than 0.33. Note that if the coefficient of variation is greater than 0.33, either the normality of the data is suspect or the probability of negative values in the data is non-neglible. In this case, McKay's approximation may not be valid. Also, it is generally recommended that the sample size should be at least 10 before using McKay's approximation.

   This method can be specified with the command

   SET COEFFICIENT OF VARIATION CONFIDENCE LIMIT METHOD ...             MCKAY

3. Vangel proposed the following modification to McKay's method.

   \[ \mbox{lcl} = \frac{K} {\sqrt{\left( \frac{u_1 + 2}{n} - 1 \right) K^2 + \frac{u_1}{n-1}}} \]

   \[ \mbox{ucl} = \frac{K} {\sqrt{\left( \frac{u_2 + 2}{n} - 1 \right) K^2 + \frac{u_2}{n-1}}} \]

   where

   \[ u_1 = \chi^2_{1 - \alpha/2,n-1} \]

   \[ u_2 = \chi^2_{\alpha/2,n-1} \]

   Vangel's modified McKay method is more accurate than the McKay in most cases, particilarly for small samples.. According to Vangel, the unmodified McKay is only more accurate when both the coefficient of variation and alpha are large. However, if the coefficient of variation is large, then this implies either that the data contains negative values or the data does not follow a normal distribution. In this case, neither the McKay or the modified McKay should be used.

   In general, the Vangel's modified McKay method is recommended over the McKay method. It generally provides good approximations as long as the data is approximately normal and the coefficient of variation is less than 0.33.

   This is the default method.

   This method can be specified with the command

   SET COEFFICIENT OF VARIATION CONFIDENCE LIMIT METHOD ...             VANGEL

4. Panichkitkitkosolkul proposed the maximum likelihood based method. This uses Vangel's formula. However, it replaces the sample coefficient of variation with the maximum likelihood estimate of the coefficient of variation. Specifically,

   \[ K = \frac{\sqrt{\sum_{i=1}^{n}{(X_i - \bar{x})^2}}} {\sqrt{n} \bar{x}} \]

   That is, we use the n rathar than (n-1) in the denominator when computing the standard deviation.

   As with the McKay and modified McKay methods, it is recommended that this method only be used when the coefficient of variation is less than 0.33 and the data are normally distributed.

   This method can be specified with the command

   SET COEFFICIENT OF VARIATION CONFIDENCE LIMIT METHOD ...
               MAXIMUM LIKELIHOOD

5. McKay also provided an exact method. The exact method involves solving a non-linear equation with the non-central t distribution. The details are given in the McKay and Verrill papers. Verrill also provides a Fortran code for implementing the exact method. Dataplot's implementation is based on this code.

   Verrill gives justification for preferring the exact method to the McKay and modified McKay approximations. If the coefficient of variation is greater than 0.33 the exact method is preferred to the McKay and modified McKay approximations. If the sample size is greater than 3,000, the exact method reverts to the Vangel modified McKay method.

   This method can be specified with the command

   SET COEFFICIENT OF VARIATION CONFIDENCE LIMIT METHOD ...             EXACT

6. Liu proposed a generalized confidence interval approach. The details for this method are given in her paper.

   This method can be specified with the command

   SET COEFFICIENT OF VARIATION CONFIDENCE LIMIT METHOD ...             GPQ

The default method is the Vangel method. For most applications, this choice should be reasonable as long as the data are approximately normally distributed.

If the data follow a lognormal distribution, then a confidence interval for the coefficient of variation is

\[ \mbox{lcl} = \sqrt{\exp(a_L) - 1} \]

\[ \mbox{ucl} = \sqrt{\exp(a_U) - 1} \]

where

\( a_L \)	=	\( \frac{(n-1)S_{n}^{2}} {\chi_{n-1,1-\alpha/2}} \)
\( a_U \)	=	\( \frac{(n-1)S_{n}^{2}} {\chi_{n-1,\alpha/2}} \)
\( S_{n}^2 \)	=	the variance of the log of the data

The derivation of this is given in the Koopmans, Owen and Rosenblatt and the Verrill papers.

<LOWER/UPPER> <LOGNORMAL> COEFFICIENT OF VARIATION
                        CONFIDENCE LIMITS <y>
                        <SUBSET/EXCEPT/FOR qualification>
where <y> is the response variable;
and where the <SUBSET/EXCEPT/FOR qualification> is optional.

If LOWER is specified, a one-sided lower confidence limit is returned. If UPPER is specified, a one-sided upper confidence limit is returned. If neither is specified, a two-sided limit is returned.

If LOGNORMAL is specified, the formula for the log normal-based confidence limits are used. If LOGNORMAL is omitted, the formulas for the normal-based confidence limits are used.

This syntax supports matrix arguments for the response variable.

MULTIPLE <LOWER/UPPER> <LOGNORMAL> COEFFICIENT OF
                        VARIATION CONFIDENCE LIMITS <y1> ... <yk>
                        <SUBSET/EXCEPT/FOR qualification>
where <y1> .... <yk> is a list of 1 to 30 response variables;
and where the <SUBSET/EXCEPT/FOR qualification> is optional.

This syntax will generate a confidence interval for each of the response variables. The word MULTIPLOT is optional. That is,

MULTIPLE COEFFICIENT OF VARIATION CONFIDENCE LIMITS ...
            Y1 Y2 Y3

is equivalent to

COEFFICIENT OF VARIATION CONFIDENCE LIMITS Y1 Y2 Y3

You can also use the TO syntax as in

COEFFICIENT OF VARIATION CONFIDENCE LIMITS Y1 TO Y10

If LOWER is specified, a one-sided lower confidence limit is returned. If UPPER is specified, a one-sided upper confidence limit is returned. If neither is specified, a two-sided limit is returned.

If LOGNORMAL is specified, the formula for the log normal-based confidence limits are used. If LOGNORMAL is omitted, the formulas for the normal-based confidence limits are used.

This syntax supports matrix arguments for the response variables.

REPLICATED <LOWER/UPPER> <LOGNORMAL> COEFFICIENT OF
                        VARIATION CONFIDENCE LIMITS <y> <x1> ... <xk>
                        <SUBSET/EXCEPT/FOR qualification>
where <y> is the response variable;
            <x1> .... <xk> is a list of 1 to 6 group-id variables;
and where the <SUBSET/EXCEPT/FOR qualification> is optional.

This syntax performs a cross-tabulation of the <x1> ... <xk> and generates a confidence interval for each unique combination of the cross-tabulated values. For example, if X1 has three levels and X2 has two levels, six confidence intervals will be generated.

If LOWER is specified, a one-sided lower confidence limit is returned. If UPPER is specified, a one-sided upper confidence limit is returned. If neither is specified, a two-sided limit is returned.

If LOGNORMAL is specified, the formula for the log normal-based confidence limits are used. If LOGNORMAL is omitted, the formulas for the normal-based confidence limits are used.

This syntax does not support matrix arguments.

COEFFICIENT OF VARIATION CONFIDENCE LIMITS Y1
COEFFICIENT OF VARIATION CONFIDENCE LIMITS Y1 SUBSET TAG > 2
MULTIPLE COEFFICIENT OF VARIATION CONFIDENCE LIMITS Y1 TO Y5
REPLICATED COEFFICIENT OF VARIATION CONFIDENCE LIMITS Y X

A table of confidence limits is printed for alpha levels of 50.0, 80.0, 90.0, 95.0, 99.0, and 99.9. If the exact method is specified, the 99.9 level is omitted.

In addition to the COEFFICIENT OF VARIATION CONFIDENCE LIMIT command, the following commands can also be used:
LET ALPHA = 0.05


LET A = LOWER COEFFICIENT OF VARIATION CONFIDENCE LIMIT Y
LET A = UPPPER COEFFICIENT OF VARIATION CONFIDENCE LIMIT Y
LET A = LOWER ONESIDED COEFFICIENT OF VARIATION ...
            CONFIDENCE LIMIT Y
LET A = UPPER ONESIDED COEFFICIENT OF VARIATION ...
            CONFIDENCE LIMIT Y


LET A = SUMMARY LOWER COEFFICIENT OF VARIATION ...
            CONFIDENCE LIMIT YMEAN YSD N
LET A = SUMMARY UPPPER COEFFICIENT OF VARIATION ...
            CONFIDENCE LIMIT YMEAN YSD N


The first command specifies the significance level. The next four commands are used when you have raw data. The last two commands are used when only summary data (mean, standard deviation, sample size) is available.

In addition to the above LET commands, built-in statistics are supported for 20+ different commands (enter HELP STATISTICS for details).

None

CONFIDENCE INTERVAL is a synonym for CONFIDENCE LIMITS

COEFFICIENT OF VARIATION	=	Compute the coefficient of variation.
CONFIDENCE LIMITS	=	Generate a confidence limit for the mean.
SD CONFIDENCE LIMITS	=	Generate a confidence limit for the standard deviation.
PREDICTION LIMITS	=	Generate prediction limits for the mean.
TOLERANCE LIMITS	=	Generate a tolerance limit.

McKay (1932), "Distributions of the Coefficient of Variation and the Extended 't' Distribution", Journal of the Royal Statistical Society, Vol. 95, pp. 695-698.

Koopmans, Owen, and Rosenblatt (1964), "Confidence Intervals for the Coefficient of Variation for the Normal and Log Normal Distributions", Biometrika, 51, 1, pp. 25-31.

Mark Vangel (1996), "Confidence Intervals for a Normal Coefficient of Variation", American Statistician, Vol. 15, No. 1, pp. 21-26.

Panichkitkitkosolkul (2009), "Improved Confidence Intervals for a Coefficient of Variation of a Normal Distribution", Thailand Statistician, 7(2), pp. 193-199.

Steve Verrill (2003), "Confidence Bounds for Normal and Lognormal Distribution Coefficients of Variation", Research Paper 609, USDA Forest Products Laboratory, Madison, Wisconsin.

Verrill, S. and Johnson, R.A. (2007), "Confidence Bounds and Hypothesis Tests for Normal Distribution Coefficients of Variation", Communications in Statistics Theory and Methods, Volume 36, No. 12, pp 2187-2206.

Liu (2012), "Confidence Interval Estimation for Coefficient of Variation", Thesis, Georgia State University, http://scholarworks.gsu.edu/math_theses/124.

Confirmatory Data Analysis

2017/01

 
SKIP 25
READ ZARR13.DAT Y
SET WRITE DECIMALS 5
.
COEFFICIENT OF VARIATION CONFIDENCE LIMITS Y
LOWER COEFFICIENT OF VARIATION CONFIDENCE LIMITS Y
UPPER COEFFICIENT OF VARIATION CONFIDENCE LIMITS Y
    

The following output is generated

            Two-Sided Confidence Limits for the Coefficient of Variation
                           for Normally Distributed Data
 
Method: Vangel (Modified McKay)
Response Variable: Y
 
Summary Statistics:
Number of Observations:                  195
Sample Mean:                             9.26146
Sample Standard Deviation:               0.02279
Sample Coefficient of Variation:         0.00246
 
 
 
---------------------------------------------------------
  Confidence    Coefficient          Lower          Upper
   Value (%)   of Variation          Limit          Limit
---------------------------------------------------------
        50.0        0.00246        0.00238        0.00255
        80.0        0.00246        0.00231        0.00263
        90.0        0.00246        0.00227        0.00269
        95.0        0.00246        0.00224        0.00273
        99.0        0.00246        0.00217        0.00283
        99.9        0.00246        0.00210        0.00294
 
 
            One-Sided Lower Confidence Limits for the Coefficient
                of Variation (for Normally Distributed Data)
 
Method: Vangel (Modified McKay)
Response Variable: Y
 
Summary Statistics:
Number of Observations:                  195
Sample Mean:                             9.26146
Sample Standard Deviation:               0.02279
Sample Coefficient of Variation:         0.00246
 
 
 
------------------------------------------
  Confidence    Coefficient          Lower
   Value (%)   of Variation          Limit
------------------------------------------
        50.0        0.00246        0.00246
        80.0        0.00246        0.00236
        90.0        0.00246        0.00231
        95.0        0.00246        0.00227
        99.0        0.00246        0.00220
        99.9        0.00246        0.00212
 
 
            One-Sided Upper Confidence Limits for the Coefficient
                of Variation (for Normally Distributed Data)
 
Method: Vangel (Modified McKay)
Response Variable: Y
 
Summary Statistics:
Number of Observations:                  195
Sample Mean:                             9.26146
Sample Standard Deviation:               0.02279
Sample Coefficient of Variation:         0.00246
 
 
 
------------------------------------------
  Confidence    Coefficient          Upper
   Value (%)   of Variation          Limit
------------------------------------------
        50.0        0.00246        0.00246
        80.0        0.00246        0.00257
        90.0        0.00246        0.00263
        95.0        0.00246        0.00269
        99.0        0.00246        0.00279
        99.9        0.00246        0.00291
    

 
. Step 1:   Create the data
.
let y = data 326 302 307 299 329
set write decimals 4
.
. Step 2:   Compute the built-in intervals
.
let cvlow = lower coefficient of variation confidence limit y
let cvupp = upper coefficient of variation confidence limit y
set coefficient of variation confidence limit method mckay
let cvlow2 = lower coefficient of variation confidence limit y
let cvupp2 = upper coefficient of variation confidence limit y
set coefficient of variation confidence limit method maximum likelihood
let cvlow3 = lower coefficient of variation confidence limit y
let cvupp3 = upper coefficient of variation confidence limit y
set coefficient of variation confidence limit method naive
let cvlow6 = lower coefficient of variation confidence limit y
let cvupp6 = upper coefficient of variation confidence limit y
set coefficient of variation confidence limit method gpq
let cvlow7 = lower coefficient of variation confidence limit y
let cvupp7 = upper coefficient of variation confidence limit y
set coefficient of variation confidence limit method exact
let cvlow8 = lower coefficient of variation confidence limit y
let cvupp8 = upper coefficient of variation confidence limit y
let cvlow9 = lower onesided coefficient of variation confidence limit y
let cvupp9 = upper onesided coefficient of variation confidence limit y
.
print "Vangel Method"
print cvlow cvupp
print " "
print "McKay Method"
print cvlow2 cvupp2
print " "
print "Maximum Likelihood Method"
print cvlow3 cvupp3
print " "
print "Naive Method"
print cvlow6 cvupp6
print " "
print "GPQ Method"
print cvlow7 cvupp7
print " "
print "Exact Method"
print cvlow8 cvupp8
print " "
.
print "Exact Method: One-Sided"
print cvlow9 cvupp9
print " "
.
set coefficient of variation confidence limit method vangel
coefficient of variation confidence limits y
    

The following output is generated

Vangel Method

 PARAMETERS AND CONSTANTS--

    CVLOW   --         0.0267
    CVUPP   --         0.1287
 
McKay Method

 PARAMETERS AND CONSTANTS--

    CVLOW2  --         0.0267
    CVUPP2  --         0.1291
 
Maximum Likelihood Method

 PARAMETERS AND CONSTANTS--

    CVLOW3  --         0.0239
    CVUPP3  --         0.1150
 
Naive Method

 PARAMETERS AND CONSTANTS--

    CVLOW6  --         0.0267
    CVUPP6  --         0.1281
 
GPQ Method

 PARAMETERS AND CONSTANTS--

    CVLOW7  --         0.0268
    CVUPP7  --         0.1306
 
Exact Method

 PARAMETERS AND CONSTANTS--

    CVLOW8  --         0.0267
    CVUPP8  --         0.1287
 
Exact Method: One-Sided

 PARAMETERS AND CONSTANTS--

    CVLOW9  --         0.0289
    CVUPP9  --         0.1061
 
 
            Two-Sided Confidence Limits for the Coefficient of Variation
                           for Normally Distributed Data
 
Method: Vangel (Modified McKay)
Response Variable: Y
 
Summary Statistics:
Number of Observations:                  5
Sample Mean:                             312.6000
Sample Standard Deviation:               13.9392
Sample Coefficient of Variation:         0.0446
 
 
 
---------------------------------------------------------
  Confidence    Coefficient          Lower          Upper
   Value (%)   of Variation          Limit          Limit
---------------------------------------------------------
        50.0         0.0446         0.0384         0.0643
        80.0         0.0446         0.0320         0.0866
        90.0         0.0446         0.0289         0.1061
        95.0         0.0446         0.0267         0.1287
        99.0         0.0446         0.0231         0.1982
        99.9         0.0446         0.0199         0.3664
    

 
SKIP 25
READ GEAR.DAT Y X
LET NNEW = 3
.
REPLICATED COEFFICIENT OF VARIATION CONFIDENCE LIMITS Y X
    

The following output is generated

            Two-Sided Confidence Limits for the Coefficient of Variation
                           for Normally Distributed Data
 
Method: Vangel (Modified McKay)
Response Variable: Y
Factor Variable 1: X                     1.00000
 
Summary Statistics:
Number of Observations:                  10
Sample Mean:                             0.99800
Sample Standard Deviation:               0.00435
Sample Coefficient of Variation:         0.00435
 
 
 
---------------------------------------------------------
  Confidence    Coefficient          Lower          Upper
   Value (%)   of Variation          Limit          Limit
---------------------------------------------------------
        50.0        0.00435        0.00387        0.00000
        80.0        0.00435        0.00341        0.00640
        90.0        0.00435        0.00318        0.00716
        95.0        0.00435        0.00300        0.00795
        99.0        0.00435        0.00269        0.00992
        99.9        0.00435        0.00240        0.01325
 
 
            Two-Sided Confidence Limits for the Coefficient of Variation
                           for Normally Distributed Data
 
Method: Vangel (Modified McKay)
Response Variable: Y
Factor Variable 1: X                     2.00000
 
Summary Statistics:
Number of Observations:                  10
Sample Mean:                             0.99910
Sample Standard Deviation:               0.00522
Sample Coefficient of Variation:         0.00522
 
 
 
---------------------------------------------------------
  Confidence    Coefficient          Lower          Upper
   Value (%)   of Variation          Limit          Limit
---------------------------------------------------------
        50.0        0.00522        0.00464        0.00000
        80.0        0.00522        0.00409        0.00767
        90.0        0.00522        0.00381        0.00859
        95.0        0.00522        0.00359        0.00953
        99.0        0.00522        0.00322        0.01189
        99.9        0.00522        0.00288        0.01589
 
 
            Two-Sided Confidence Limits for the Coefficient of Variation
                           for Normally Distributed Data
 
Method: Vangel (Modified McKay)
Response Variable: Y
Factor Variable 1: X                     3.00000
 
Summary Statistics:
Number of Observations:                  10
Sample Mean:                             0.99540
Sample Standard Deviation:               0.00398
Sample Coefficient of Variation:         0.00400
 
 
 
---------------------------------------------------------
  Confidence    Coefficient          Lower          Upper
   Value (%)   of Variation          Limit          Limit
---------------------------------------------------------
        50.0        0.00400        0.00355        0.00000
        80.0        0.00400        0.00313        0.00587
        90.0        0.00400        0.00291        0.00657
        95.0        0.00400        0.00275        0.00730
        99.0        0.00400        0.00247        0.00910
        99.9        0.00400        0.00220        0.01216
 
 
            Two-Sided Confidence Limits for the Coefficient of Variation
                           for Normally Distributed Data
 
Method: Vangel (Modified McKay)
Response Variable: Y
Factor Variable 1: X                     4.00000
 
Summary Statistics:
Number of Observations:                  10
Sample Mean:                             0.99820
Sample Standard Deviation:               0.00385
Sample Coefficient of Variation:         0.00386
 
 
 
---------------------------------------------------------
  Confidence    Coefficient          Lower          Upper
   Value (%)   of Variation          Limit          Limit
---------------------------------------------------------
        50.0        0.00386        0.00343        0.00000
        80.0        0.00386        0.00302        0.00567
        90.0        0.00386        0.00282        0.00635
        95.0        0.00386        0.00265        0.00705
        99.0        0.00386        0.00238        0.00879
        99.9        0.00386        0.00213        0.01175
 
 
            Two-Sided Confidence Limits for the Coefficient of Variation
                           for Normally Distributed Data
 
Method: Vangel (Modified McKay)
Response Variable: Y
Factor Variable 1: X                     5.00000
 
Summary Statistics:
Number of Observations:                  10
Sample Mean:                             0.99190
Sample Standard Deviation:               0.00758
Sample Coefficient of Variation:         0.00764
 
 
 
---------------------------------------------------------
  Confidence    Coefficient          Lower          Upper
   Value (%)   of Variation          Limit          Limit
---------------------------------------------------------
        50.0        0.00764        0.00679        0.00000
        80.0        0.00764        0.00598        0.01123
        90.0        0.00764        0.00557        0.01257
        95.0        0.00764        0.00526        0.01395
        99.0        0.00764        0.00472        0.01740
        99.9        0.00764        0.00421        0.02326
 
 
            Two-Sided Confidence Limits for the Coefficient of Variation
                           for Normally Distributed Data
 
Method: Vangel (Modified McKay)
Response Variable: Y
Factor Variable 1: X                     6.00000
 
Summary Statistics:
Number of Observations:                  10
Sample Mean:                             0.99880
Sample Standard Deviation:               0.00989
Sample Coefficient of Variation:         0.00990
 
 
 
---------------------------------------------------------
  Confidence    Coefficient          Lower          Upper
   Value (%)   of Variation          Limit          Limit
---------------------------------------------------------
        50.0        0.00990        0.00880        0.00000
        80.0        0.00990        0.00775        0.01454
        90.0        0.00990        0.00722        0.01629
        95.0        0.00990        0.00681        0.01807
        99.0        0.00990        0.00611        0.02255
        99.9        0.00990        0.00545        0.03013
 
 
            Two-Sided Confidence Limits for the Coefficient of Variation
                           for Normally Distributed Data
 
Method: Vangel (Modified McKay)
Response Variable: Y
Factor Variable 1: X                     7.00000
 
Summary Statistics:
Number of Observations:                  10
Sample Mean:                             1.00150
Sample Standard Deviation:               0.00788
Sample Coefficient of Variation:         0.00787
 
 
 
---------------------------------------------------------
  Confidence    Coefficient          Lower          Upper
   Value (%)   of Variation          Limit          Limit
---------------------------------------------------------
        50.0        0.00787        0.00699        0.00000
        80.0        0.00787        0.00616        0.01156
        90.0        0.00787        0.00574        0.01294
        95.0        0.00787        0.00541        0.01436
        99.0        0.00787        0.00486        0.01792
        99.9        0.00787        0.00433        0.02394
 
 
            Two-Sided Confidence Limits for the Coefficient of Variation
                           for Normally Distributed Data
 
Method: Vangel (Modified McKay)
Response Variable: Y
Factor Variable 1: X                     8.00000
 
Summary Statistics:
Number of Observations:                  10
Sample Mean:                             1.00040
Sample Standard Deviation:               0.00363
Sample Coefficient of Variation:         0.00363
 
 
 
---------------------------------------------------------
  Confidence    Coefficient          Lower          Upper
   Value (%)   of Variation          Limit          Limit
---------------------------------------------------------
        50.0        0.00363        0.00322        0.00000
        80.0        0.00363        0.00284        0.00533
        90.0        0.00363        0.00264        0.00596
        95.0        0.00363        0.00249        0.00662
        99.0        0.00363        0.00224        0.00826
        99.9        0.00363        0.00200        0.01103
 
 
            Two-Sided Confidence Limits for the Coefficient of Variation
                           for Normally Distributed Data
 
Method: Vangel (Modified McKay)
Response Variable: Y
Factor Variable 1: X                     9.00000
 
Summary Statistics:
Number of Observations:                  10
Sample Mean:                             0.99830
Sample Standard Deviation:               0.00414
Sample Coefficient of Variation:         0.00414
 
 
 
---------------------------------------------------------
  Confidence    Coefficient          Lower          Upper
   Value (%)   of Variation          Limit          Limit
---------------------------------------------------------
        50.0        0.00414        0.00368        0.00000
        80.0        0.00414        0.00325        0.00609
        90.0        0.00414        0.00302        0.00682
        95.0        0.00414        0.00285        0.00757
        99.0        0.00414        0.00256        0.00944
        99.9        0.00414        0.00228        0.01262
 
 
            Two-Sided Confidence Limits for the Coefficient of Variation
                           for Normally Distributed Data
 
Method: Vangel (Modified McKay)
Response Variable: Y
Factor Variable 1: X                     10.00000
 
Summary Statistics:
Number of Observations:                  10
Sample Mean:                             0.99480
Sample Standard Deviation:               0.00533
Sample Coefficient of Variation:         0.00536
 
 
 
---------------------------------------------------------
  Confidence    Coefficient          Lower          Upper
   Value (%)   of Variation          Limit          Limit
---------------------------------------------------------
        50.0        0.00536        0.00476        0.00000
        80.0        0.00536        0.00419        0.00787
        90.0        0.00536        0.00391        0.00881
        95.0        0.00536        0.00368        0.00978
        99.0        0.00536        0.00331        0.01220
        99.9        0.00536        0.00295        0.01630
    

 
skip 25
read LGN.DAT
.
let lcv  = lognormal coef of vari y
let lcvl = lower lognormal coef of vari conf limit y
let ucvl = upper lognormal coef of vari conf limit y
.
set write decimals 3
print lcv lcvl ucvl
.
lognormal coefficient of variation confidence limits y
    

The following output is generated

 PARAMETERS AND CONSTANTS--

     LCV     --  0.1923724E+02
     LCVL    --  0.5442615E+01
     UCVL    --  0.5503915E+03
 
            Two-Sided Confidence Limits for the Coefficient of Variation
                          for Lognormally Distributed Data
 
Method: Koopmans, Owen, and Rosenblatt
Response Variable: Y
 
Summary Statistics:
Number of Observations:                  20
Sample Mean (Log of Data):                0.5866234E-01
Sample Standard Deviation (Log of Data):  0.2432364E+01
Sample Coefficient of Variation:          0.1923724E+02
 
 
 
---------------------------------------------------------
  Confidence    Coefficient          Lower          Upper
   Value (%)   of Variation          Limit          Limit
---------------------------------------------------------
        50.0  0.1923724E+02  0.1182862E+02  0.4744320E+02
        80.0  0.1923724E+02  0.7830511E+01  0.1244767E+03
        90.0  0.1923724E+02  0.6375431E+01  0.2586717E+03
        95.0  0.1923724E+02  0.5442615E+01  0.5503915E+03
        99.0  0.1923724E+02  0.4173985E+01  0.3686548E+04
        99.9  0.1923724E+02  0.3245359E+01  0.9312940E+05