INSET keywords </ options>;
An INSET statement places a box or table of summary statistics, called an inset, directly in a graph created with a CDFPLOT, HISTOGRAM, PPPLOT, PROBPLOT, or QQPLOT statement. The INSET statement must follow the plot statement that creates the plot that you want to augment. The inset appears in all the graphs that the preceding plot statement produces.
You can use multiple INSET statements after a plot statement to add more than one inset to a plot. See Example 4.17.
In an INSET statement, you specify one or more keywords that identify the information to display in the inset. The information is displayed in the order that you request the keywords. Keywords can be any of the following:
statistical keywords
primary keywords
secondary keywords
The available statistical keywords are listed in Table 4.10.
Table 4.10: Statistical Keywords
Keyword 
Description 

Descriptive Statistic Keywords 

CSS 
Corrected sum of squares 
CV 
Coefficient of variation 
GEOMEAN 
Geometric mean 
KURTOSIS  KURT 
Kurtosis 
MAX 
Largest value 
MEAN 
Sample mean 
MIN 
Smallest value 
MODE 
Most frequent value 
N 
Sample size 
NEXCL 
Number of observations excluded by MAXNBIN= or MAXSIGMAS= option 
NMISS 
Number of missing values 
NOBS 
Number of observations 
RANGE 
Range 
SKEWNESS  SKEW 
Skewness 
STD  STDDEV 
Standard deviation 
STDMEAN  STDERR 
Standard error of the mean 
SUM 
Sum of the observations 
SUMWGT 
Sum of the weights 
USS 
Uncorrected sum of squares 
VAR 
Variance 
Percentile Statistic Keywords 

P1 
1st percentile 
P5 
5th percentile 
P10 
10th percentile 
Q1 

P25 
Lower quartile (25th percentile) 
MEDIAN 

Q2 

P50 
Median (50th percentile) 
Q3 

P75 
Upper quartile (75th percentile) 
P90 
90th percentile 
P95 
95th percentile 
P99 
99th percentile 
QRANGE 
Interquartile range (Q3–Q1) 
Keywords for DistributionFree Confidence Limits for Percentiles (CIPCTLDF Option) 

P1_LCL_DF 
1st percentile lower confidence limit 
P1_UCL_DF 
1st percentile upper confidence limit 
P5_LCL_DF 
5th percentile lower confidence limit 
P5_UCL_DF 
5th percentile upper confidence limit 
P10_LCL_DF 
10th percentile lower confidence limit 
P10_UCL_DF 
10th percentile upper confidence limit 
Q1_LCL_DF 

P25_LCL_DF 
Lower quartile (25th percentile) lower confidence limit 
Q1_UCL_DF 

P25_UCL_DF 
Lower quartile (25th percentile) upper confidence limit 
MEDIAN_LCL_DF 

Q2_LCL_DF 

P50_LCL_DF 
Median (50th percentile) lower confidence limit 
MEDIAN_UCL_DF 

Q2_UCL_DF 

P50_UCL_DF 
Median (50th percentile) upper confidence limit 
Q3_LCL_DF 

P75_LCL_DF 
Upper quartile (75th percentile) lower confidence limit 
Q3_UCL_DF 

P75_UCL_DF 
Upper quartile (75th percentile) upper confidence limit 
P90_LCL_DF 
90th percentile lower confidence limit 
P90_UCL_DF 
90th percentile upper confidence limit 
P95_LCL_DF 
95th percentile lower confidence limit 
P95_UCL_DF 
95th percentile upper confidence limit 
P99_LCL_DF 
99th percentile lower confidence limit 
P99_UCL_DF 
99th percentile upper confidence limit 
Keywords Percentile Confidence Limits Assuming Normality (CIPCTLNORMAL Option) 

P1_LCL 
1st percentile lower confidence limit 
P1_UCL 
1st percentile upper confidence limit 
P5_LCL 
5th percentile lower confidence limit 
P5_UCL 
5th percentile upper confidence limit 
P10_LCL 
10th percentile lower confidence limit 
P10_UCL 
10th percentile upper confidence limit 
Q1_LCL 

P25_LCL 
Lower quartile (25th percentile) lower confidence limit 
Q1_UCL 

P25_UCL 
Lower quartile (25th percentile) upper confidence limit 
MEDIAN_LCL 

Q2_LCL 

P50_LCL 
Median (50th percentile) lower confidence limit 
MEDIAN_UCL 

Q2_UCL 

P50_UCL 
Median (50th percentile) upper confidence limit 
Q3_LCL 

P75_LCL 
Upper quartile (75th percentile) lower confidence limit 
Q3_UCL 

P75_UCL 
Upper quartile (75th percentile) upper confidence limit 
P90_LCL 
90th percentile lower confidence limit 
P90_UCL 
90th percentile upper confidence limit 
P95_LCL 
95th percentile lower confidence limit 
P95_UCL 
95th percentile upper confidence limit 
P99_LCL 
99th percentile lower confidence limit 
P99_UCL 
99th percentile upper confidence limit 
Robust Statistics Keywords 

GINI 
Gini’s mean difference 
MAD 
Median absolute difference about the median 
QN 

SN 

STD_GINI 
Gini’s standard deviation 
STD_MAD 
MAD standard deviation 
STD_QN 

STD_QRANGE 
Interquartile range standard deviation 
STD_SN 

Hypothesis Testing Keywords 

MSIGN 
Sign statistic 
NORMALTEST 
Test statistic for normality 
PNORMAL 
Probability value for the test of normality 
SIGNRANK 
Signed rank statistic 
PROBM 
Probability of greater absolute value for the sign statistic 
PROBN 
Probability value for the test of normality 
PROBS 
Probability value for the signed rank test 
PROBT 
Probability value for the Student’s t test 
T 
Statistics for Student’s t test 
Keyword for Reading an Input Data Set 

DATA= 
(label, value) pairs from input data set 
To create a completely customized inset, use a DATA= data set.
A primary keyword specifies a fitted distribution, which is one of the parametric distributions or a kernel density estimate. You specify secondary keywords in parentheses after the primary keyword to request particular statistics associated with that distribution.
Note: When producing traditional graphics output, you can specify a primary keyword without secondary keywords to display a colored line and the distribution name as a key for the density curve.
In the HISTOGRAM statement you can request more than one fitted distribution from the same family (for example, two normal distributions). You can display inset statistics for individual curves by specifying the curve indices in square brackets immediately following the primary keyword.
The following statements produce a histogram with three fitted normal curves and an inset that contains goodnessoffit statistics for the second curve only:
proc univariate data=score; histogram final / normal(sigma=1 2 3); inset normal[2](ad adpval); run;
Table 4.11 lists the primary keywords and the plot statements with which they can be specified.
Table 4.11: Primary Keywords
Keyword 
Distribution 
Plot Statement Availability 

BETA 
Beta 
All plot statements 
EXPONENTIAL 
Exponential 
All plot statements 
GAMMA 
Gamma 
All plot statements 
GUMBEL 
Gumbel 
All plot statements 
IGAUSS 
Inverse Gaussian 
CDFPLOT, HISTOGRAM, PPPLOT 
KERNEL 
Kernel density estimate 
HISTOGRAM 
LOGNORMAL 
Lognormal 
All plot statements 
NORMAL 
Normal 
All plot statements 
PARETO 
Pareto 
All plot statements 
POWER 
Power function 
All plot statements 
RAYLEIGH 
Rayleigh 
All plot statements 
SB 
HISTOGRAM 

SU 
HISTOGRAM 

WEIBULL 
Weibull(3parameter) 
All plot statements 
WEIBULL2 
Weibull(2parameter) 
PROBPLOT, QQPLOT 
Table 4.12 lists the secondary keywords available with the primary keywords listed in Table 4.11.
Table 4.12: Secondary Keywords
Secondary Keyword 
Alias 
Description 

BETA Secondary Keywords 

ALPHA 
SHAPE1 

BETA 
SHAPE2 

MEAN 
Mean of the fitted distribution 

SIGMA 
SCALE 

STD 
Standard deviation of the fitted distribution 

THETA 
THRESHOLD 

EXPONENTIAL Secondary Keywords 

MEAN 
Mean of the fitted distribution 

SIGMA 
SCALE 

STD 
Standard deviation of the fitted distribution 

THETA 
THRESHOLD 

GAMMA Secondary Keywords 

ALPHA 
SHAPE 

MEAN 
Mean of the fitted distribution 

SIGMA 
SCALE 

STD 
Standard deviation of the fitted distribution 

THETA 
THRESHOLD 

GUMBEL Secondary Keywords 

MEAN 
Mean of the fitted distribution 

MU 

SIGMA 
SCALE 

STD 
Standard deviation of the fitted distribution 

IGAUSS Secondary Keywords 

LAMBDA 

MEAN 
Mean of the fitted distribution 

MU 

STD 
Standard deviation of the fitted distribution 

KERNEL Secondary Keywords 

AMISE 
Approximate mean integrated square error (MISE) for the kernel density 

BANDWIDTH 

BWIDTH 
Alias for BANDWIDTH 

C 
Standardized bandwidth for the density estimate 

TYPE 
Kernel type: normal, quadratic, or triangular 

LOGNORMAL Secondary Keywords 

MEAN 
Mean of the fitted distribution 

SIGMA 
SHAPE 

STD 
Standard deviation of the fitted distribution 

THETA 
THRESHOLD 

ZETA 
SCALE 

NORMAL Secondary Keywords 

MU 
MEAN 

SIGMA 
STD 

PARETO Secondary Keywords 

ALPHA 

MEAN 
Mean of the fitted distribution 

SIGMA 
SCALE 

STD 
Standard deviation of the fitted distribution 

THETA 
THRESHOLD 

POWER Secondary Keywords 

ALPHA 

MEAN 
Mean of the fitted distribution 

SIGMA 
SCALE 

STD 
Standard deviation of the fitted distribution 

THETA 
THRESHOLD 

RAYLEIGH Secondary Keywords 

MEAN 
Mean of the fitted distribution 

SIGMA 
SCALE 

STD 
Standard deviation of the fitted distribution 

THETA 
THRESHOLD 

SB and SU Secondary Keywords 

DELTA 
SHAPE1 

GAMMA 
SHAPE2 

MEAN 
Mean of the fitted distribution 

SIGMA 
SCALE 

STD 
Standard deviation of the fitted distribution 

THETA 
THRESHOLD 

WEIBULL Secondary Keywords 

C 
SHAPE 
Shape parameter c 
MEAN 
Mean of the fitted distribution 

SIGMA 
SCALE 

STD 
Standard deviation of the fitted distribution 

THETA 
THRESHOLD 

WEIBULL2 Secondary Keywords 

C 
SHAPE 
Shape parameter c 
MEAN 
Mean of the fitted distribution 

SIGMA 
SCALE 

STD 
Standard deviation of the fitted distribution 

THETA 
THRESHOLD 

Keywords Available for All Parametric (nonKERNEL) Distributions 

AD 
AndersonDarling EDF test statistic 

ADPVAL 
AndersonDarling EDF test pvalue 

CVM 
Cramér–von Mises EDF test statistic 

CVMPVAL 
Cramér–von Mises EDF test pvalue 

KSD 
KolmogorovSmirnov EDF test statistic 

KSDPVAL 
KolmogorovSmirnov EDF test pvalue 
The inset statistics listed in Table 4.12 are not available unless you request a plot statement and options that calculate these statistics. For example, consider the following statements:
proc univariate data=score; histogram final / normal; inset mean std normal(ad adpval); run;
The MEAN and STD keywords display the sample mean and standard deviation, respectively, of final
. The NORMAL keyword with the secondary keywords AD and ADPVAL displays the AndersonDarling goodnessoffit test statistic
and pvalue, respectively. The statistics that are specified with the NORMAL keyword are available only because the NORMAL option is requested in the HISTOGRAM statement.
The KERNEL keyword is available only if you request a kernel density estimate in a HISTOGRAM statement. The WEIBULL2 keyword is available only if you request a twoparameter Weibull distribution in the PROBPLOT or QQPLOT statement.
By default, PROC UNIVARIATE identifies inset statistics with appropriate labels and prints numeric values with appropriate formats. To customize the label, specify the keyword followed by an equal sign (=) and the desired label in quotes. To customize the format, specify a numeric format in parentheses after the keyword. Labels can have up to 24 characters. If you specify both a label and a format for a statistic, the label must appear before the format. For example, the following statement requests customized labels for two statistics and displays the standard deviation with a field width of 5 and two decimal places:
inset n='Sample Size' std='Std Dev' (5.2);
Table 4.13 lists INSET statement options, which are specified after the slash (/) in the INSET statement. For complete descriptions, see the section Dictionary of Options.
Table 4.13: INSET Options
The following entries provide detailed descriptions of options for the INSET statement. Options marked with † are applicable only when traditional graphics are produced.