AT_BANNER([EXAMINE])

AT_SETUP([EXAMINE])
AT_DATA([examine.sps], [
DATA LIST LIST /QUALITY * W * BRAND * .
BEGIN DATA
3  1  1
2  2  1
1  2  1
1  1  1
4  1  1
4  1  1
5  1  2
2  1  2
4  4  2
2  1  2
3  1  2
7  1  3
4  2  3
5  3  3
3  1  3
6  1  3
END DATA

WEIGHT BY w.

VARIABLE LABELS brand   'Manufacturer'.
VARIABLE LABELS quality 'Breaking Strain'.

VALUE LABELS /brand 1 'Aspeger' 2 'Bloggs' 3 'Charlies'.

LIST /FORMAT=NUMBERED.

EXAMINE
	quality BY brand
	/STATISTICS descriptives extreme(3)
	.
])


dnl In the following data, only the extreme values have been checked.
dnl The descriptives have been blindly pasted.
AT_CHECK([pspp -O format=csv examine.sps], [0], [dnl
Table: Reading free-form data from INLINE.
Variable,Format
QUALITY,F8.0
W,F8.0
BRAND,F8.0

Table: Data List
Case Number,QUALITY,W,BRAND
1,3.00,1.00,1.00
2,2.00,2.00,1.00
3,1.00,2.00,1.00
4,1.00,1.00,1.00
5,4.00,1.00,1.00
6,4.00,1.00,1.00
7,5.00,1.00,2.00
8,2.00,1.00,2.00
9,4.00,4.00,2.00
10,2.00,1.00,2.00
11,3.00,1.00,2.00
12,7.00,1.00,3.00
13,4.00,2.00,3.00
14,5.00,3.00,3.00
15,3.00,1.00,3.00
16,6.00,1.00,3.00

Table: Case Processing Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
Breaking Strain,24.00,100%,.00,0%,24.00,100%

Table: Extreme Values
,,,Case Number,Value
Breaking Strain,Highest,1,12,7.00
,,2,16,6.00
,,3,14,5.00
,Lowest,1,3,1.00
,,2,4,1.00
,,3,2,2.00

Table: Descriptives
,,,Statistic,Std. Error
Breaking Strain,Mean,,3.54,.32
,95% Confidence Interval for Mean,Lower Bound,2.87,
,,Upper Bound,4.21,
,5% Trimmed Mean,,3.50,
,Median,,4.00,
,Variance,,2.52,
,Std. Deviation,,1.59,
,Minimum,,1.00,
,Maximum,,7.00,
,Range,,6.00,
,Interquartile Range,,2.75,
,Skewness,,.06,.47
,Kurtosis,,-.36,.92

Table: Case Processing Summary
,,Cases,,,,,
,,Valid,,Missing,,Total,
,Manufacturer,N,Percent,N,Percent,N,Percent
Breaking Strain,Aspeger,8.00,100%,.00,0%,8.00,100%
,Bloggs,8.00,100%,.00,0%,8.00,100%
,Charlies,8.00,100%,.00,0%,8.00,100%

Table: Extreme Values
,Manufacturer,,,Case Number,Value
Breaking Strain,Aspeger,Highest,1,6,4.00
,,,2,5,4.00
,,,3,1,3.00
,,Lowest,1,3,1.00
,,,2,4,1.00
,,,3,2,2.00
,Bloggs,Highest,1,7,5.00
,,,2,9,4.00
,,,3,11,3.00
,,Lowest,1,8,2.00
,,,2,10,2.00
,,,3,11,3.00
,Charlies,Highest,1,12,7.00
,,,2,16,6.00
,,,3,14,5.00
,,Lowest,1,15,3.00
,,,2,13,4.00
,,,3,14,5.00

Table: Descriptives
,Manufacturer,,,Statistic,Std. Error
Breaking Strain,Aspeger,Mean,,2.25,.45
,,95% Confidence Interval for Mean,Lower Bound,1.18,
,,,Upper Bound,3.32,
,,5% Trimmed Mean,,2.22,
,,Median,,2.00,
,,Variance,,1.64,
,,Std. Deviation,,1.28,
,,Minimum,,1.00,
,,Maximum,,4.00,
,,Range,,3.00,
,,Interquartile Range,,2.75,
,,Skewness,,.47,.75
,,Kurtosis,,-1.55,1.48
,Bloggs,Mean,,3.50,.38
,,95% Confidence Interval for Mean,Lower Bound,2.61,
,,,Upper Bound,4.39,
,,5% Trimmed Mean,,3.50,
,,Median,,4.00,
,,Variance,,1.14,
,,Std. Deviation,,1.07,
,,Minimum,,2.00,
,,Maximum,,5.00,
,,Range,,3.00,
,,Interquartile Range,,1.75,
,,Skewness,,-.47,.75
,,Kurtosis,,-.83,1.48
,Charlies,Mean,,4.88,.44
,,95% Confidence Interval for Mean,Lower Bound,3.83,
,,,Upper Bound,5.92,
,,5% Trimmed Mean,,4.86,
,,Median,,5.00,
,,Variance,,1.55,
,,Std. Deviation,,1.25,
,,Minimum,,3.00,
,,Maximum,,7.00,
,,Range,,4.00,
,,Interquartile Range,,1.75,
,,Skewness,,.30,.75
,,Kurtosis,,.15,1.48
])

AT_CLEANUP

AT_SETUP([EXAMINE -- extremes])
AT_DATA([examine.sps], [dnl
data list free /V1 W
begin data.
1  1
2  1
3  2
3  1
4  1
5  1
6  1
7  1
8  1
9  1
10 1
11 1
12 1
13 1
14 1
15 1
16 1
17 1
18 2
19 1
20 1
end data.

weight by w.

examine v1 
 /statistics=extreme(6)
 .
])

AT_CHECK([pspp -O format=csv examine.sps], [0],[dnl
Table: Case Processing Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
V1,23.00,100%,.00,0%,23.00,100%

Table: Extreme Values
,,,Case Number,Value
V1,Highest,1,21,20.00
,,2,20,19.00
,,3,19,18.00
,,4,18,17.00
,,5,17,16.00
,,6,16,15.00
,Lowest,1,1,1.00
,,2,2,2.00
,,3,3,3.00
,,4,4,3.00
,,5,5,4.00
,,6,6,5.00
])

AT_CLEANUP



AT_SETUP([EXAMINE -- extremes with fractional weights])
AT_DATA([extreme.sps], [dnl
set format=F20.3.
data list notable list /w * x *.
begin data.
 0.88  300000
 0.86  320000
 0.98  480000
 0.93  960000
 1.35  960000
 1.31  960000
 0.88  960000
 0.88  1080000
 0.88  1080000
 0.95  1200000
 1.47  1200000
 0.93  1200000
 0.98  1320000
 1.31  1380000
 0.93  1440000
 0.88  1560000
 1.56  1560000
 1.47  1560000
end data.

weight by w.


EXAMINE
        x
        /STATISTICS = DESCRIPTIVES EXTREME (5)
        .
])

AT_CHECK([pspp -O format=csv  extreme.sps], [0], [dnl
Table: Case Processing Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
x,19.430,100%,.000,0%,19.430,100%

Table: Extreme Values
,,,Case Number,Value
x,Highest,1,18,1560000.000
,,2,17,1560000.000
,,3,16,1560000.000
,,4,15,1440000.000
,,5,14,1380000.000
,Lowest,1,1,300000.000
,,2,2,320000.000
,,3,3,480000.000
,,4,4,960000.000
,,5,5,960000.000

Table: Descriptives
,,,Statistic,Std. Error
x,Mean,,1120010.293,86222.178
,95% Confidence Interval for Mean,Lower Bound,939166.693,
,,Upper Bound,1300853.894,
,5% Trimmed Mean,,1141017.899,
,Median,,1200000.000,
,Variance,,144447748124.869,
,Std. Deviation,,380062.821,
,Minimum,,300000.000,
,Maximum,,1560000.000,
,Range,,1260000.000,
,Interquartile Range,,467258.065,
,Skewness,,-.887,.519
,Kurtosis,,.340,1.005
])

AT_CLEANUP

dnl Test the PERCENTILES subcommand of the EXAMINE command.
dnl In particular test that it behaves properly when there are only 
dnl a few cases.
AT_SETUP([EXAMINE -- percentiles])
AT_DATA([examine.sps], [dnl
DATA LIST LIST /X *.
BEGIN DATA.
2.00 
8.00 
5.00 
END DATA.

EXAMINE /x
	/PERCENTILES=HAVERAGE.

EXAMINE /x
	/PERCENTILES=WAVERAGE.

EXAMINE /x
	/PERCENTILES=ROUND.

EXAMINE /x
	/PERCENTILES=EMPIRICAL.

EXAMINE /x
	/PERCENTILES=AEMPIRICAL.
])
AT_CHECK([pspp -o pspp.csv examine.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Reading free-form data from INLINE.
Variable,Format
X,F8.0

Table: Case Processing Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
X,3,100%,0,0%,3,100%

Table: Percentiles
,,Percentiles,,,,,,
,,5,10,25,50,75,90,95
X,HAverage,.40,.80,2.00,5.00,8.00,8.00,8.00
,Tukey's Hinges,,,3.50,5.00,6.50,,

Table: Case Processing Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
X,3,100%,0,0%,3,100%

Table: Percentiles
,,Percentiles,,,,,,
,,5,10,25,50,75,90,95
X,Weighted Average,.30,.60,1.50,3.50,5.75,7.10,7.55
,Tukey's Hinges,,,3.50,5.00,6.50,,

Table: Case Processing Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
X,3,100%,0,0%,3,100%

Table: Percentiles
,,Percentiles,,,,,,
,,5,10,25,50,75,90,95
X,Rounded,.00,.00,2.00,5.00,5.00,8.00,8.00
,Tukey's Hinges,,,3.50,5.00,6.50,,

Table: Case Processing Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
X,3,100%,0,0%,3,100%

Table: Percentiles
,,Percentiles,,,,,,
,,5,10,25,50,75,90,95
X,Empirical,2.00,2.00,2.00,5.00,8.00,8.00,8.00
,Tukey's Hinges,,,3.50,5.00,6.50,,

Table: Case Processing Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
X,3,100%,0,0%,3,100%

Table: Percentiles
,,Percentiles,,,,,,
,,5,10,25,50,75,90,95
X,Empirical with averaging,2.00,2.00,2.00,5.00,8.00,8.00,8.00
,Tukey's Hinges,,,3.50,5.00,6.50,,
])
AT_CLEANUP

AT_SETUP([EXAMINE -- missing values])
AT_DATA([examine.sps], [dnl
DATA LIST LIST /x * y *.
BEGIN DATA.
1   1 
2   1
3   1
4   1
5   2
6   2
.   2
END DATA

EXAMINE /x by y
        /MISSING = PAIRWISE
        .
])
AT_CHECK([pspp -o pspp.csv examine.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Reading free-form data from INLINE.
Variable,Format
x,F8.0
y,F8.0

Table: Case Processing Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
x,6,85.7143%,1,14.2857%,7,100%

Table: Case Processing Summary
,,Cases,,,,,
,,Valid,,Missing,,Total,
,y,N,Percent,N,Percent,N,Percent
x,1.00,4,100%,0,0%,4,100%
,2.00,2,66.6667%,1,33.3333%,3,100%
])
AT_CLEANUP


AT_SETUP([EXAMINE -- user missing values])
AT_DATA([examine-m.sps], [dnl
DATA LIST notable LIST /x * y *.
BEGIN DATA.
1                   2
9999999999          2
9999999999          99
END DATA.

MISSING VALUES x (9999999999).
MISSING VALUES y (99).

EXAMINE
	/VARIABLES= x y
	/MISSING=PAIRWISE.
])
AT_CHECK([pspp -O format=csv examine-m.sps], [0], [dnl
Table: Case Processing Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
x,1,33.3333%,2,66.6667%,3,100%
y,2,66.6667%,1,33.3333%,3,100%
])
AT_CLEANUP

AT_SETUP([EXAMINE -- missing values and percentiles])
AT_DATA([examine.sps], [dnl
DATA LIST LIST /X *.
BEGIN DATA.
99
99
5.00
END DATA.

MISSING VALUE X (99).

EXAMINE /x
        /PERCENTILES=HAVERAGE.
])
AT_CHECK([pspp -o pspp.csv examine.sps])
dnl Ignore output -- this is just a no-crash check.
AT_CLEANUP

dnl Tests the trimmed mean calculation in the case
dnl where the data is weighted towards the centre.
AT_SETUP([EXAMINE -- trimmed mean])
AT_DATA([examine.sps], [dnl
DATA LIST LIST /X * C *.
BEGIN DATA.
1 1
2 49
3 2
END DATA.

WEIGHT BY c.

EXAMINE
	x
	/STATISTICS=DESCRIPTIVES
	.
])
AT_CHECK([pspp -o pspp.csv examine.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Reading free-form data from INLINE.
Variable,Format
X,F8.0
C,F8.0

Table: Case Processing Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
X,52.00,100%,.00,0%,52.00,100%

Table: Descriptives
,,,Statistic,Std. Error
X,Mean,,2.02,.03
,95% Confidence Interval for Mean,Lower Bound,1.95,
,,Upper Bound,2.09,
,5% Trimmed Mean,,2.00,
,Median,,2.00,
,Variance,,.06,
,Std. Deviation,,.24,
,Minimum,,1.00,
,Maximum,,3.00,
,Range,,2.00,
,Interquartile Range,,.00,
,Skewness,,1.19,.33
,Kurtosis,,15.73,.65
])
AT_CLEANUP

AT_SETUP([EXAMINE -- crash bug])
AT_DATA([examine.sps], [dnl
data list list /a * x * y *.
begin data.
3 1 3
5 1 4
7 2 3
end data.

examine a by x by y
	/statistics=DESCRIPTIVES
	. 
])
AT_CHECK([pspp -o pspp.csv examine.sps])
dnl Ignore output -- this is just a no-crash check.
AT_CLEANUP

dnl Test that two consecutive EXAMINE commands don't crash PSPP.
AT_SETUP([EXAMINE -- consecutive runs don't crash])
AT_DATA([examine.sps], [dnl
data list list /y * z *.
begin data.
6 4
5 3
7 6
end data.

EXAMINE /VARIABLES= z BY y.

EXAMINE /VARIABLES= z. 
])
AT_CHECK([pspp -o pspp.csv examine.sps])
dnl Ignore output -- this is just a no-crash check.
AT_CLEANUP

dnl Test that /DESCRIPTIVES does not crash in presence of missing values.
AT_SETUP([EXAMINE -- missing values don't crash])
AT_DATA([examine.sps], [dnl
data list list /x * y *.
begin data.
1 0
2 0
. 0
3 1
4 1
end data.
examine x by y /statistics=descriptives. 
])
AT_CHECK([pspp -o pspp.csv examine.sps])
dnl Ignore output -- this is just a no-crash check.
AT_CLEANUP

dnl Test that having only a single case doesn't crash.
AT_SETUP([EXAMINE -- single case doesn't crash])
AT_DATA([examine.sps], [dnl
DATA LIST LIST /quality * .
BEGIN DATA
3  
END DATA


EXAMINE
	quality 
	/STATISTICS descriptives 
        /PLOT = histogram
	.
])
AT_CHECK([pspp -o pspp.csv examine.sps], [0], [ignore])
dnl Ignore output -- this is just a no-crash check.
AT_CLEANUP

dnl Test that all-missing data doesn't crash.
AT_SETUP([EXAMINE -- all-missing data doesn't crash])
AT_DATA([examine.sps], [dnl
DATA LIST LIST /x *.
BEGIN DATA.
.
.
.
.
END DATA.

EXAMINE /x PLOT=HISTOGRAM.
])
AT_CHECK([pspp -o pspp.csv examine.sps], [0], [ignore])
dnl Ignore output -- this is just a no-crash check.
AT_CLEANUP

dnl Test that big input doesn't crash (bug 11307).
AT_SETUP([EXAMINE -- big input doesn't crash])
AT_DATA([examine.sps], [dnl
INPUT PROGRAM.
	LOOP #I=1 TO 50000.
		COMPUTE X=NORMAL(10).
		END CASE.
	END LOOP.
	END FILE.
END INPUT PROGRAM.


EXAMINE /x
	/STATISTICS=DESCRIPTIVES.
])
AT_CHECK([pspp -o pspp.csv examine.sps])
dnl Ignore output -- this is just a no-crash check.
AT_CLEANUP

dnl Another test that big input doesn't crash.
dnl The actual bug that this checks for has been lost.
AT_SETUP([EXAMINE -- big input doesn't crash 2])
AT_DATA([make-big-input.pl], 
  [for ($i=0; $i<100000; $i++) { print "AB12\n" };
   for ($i=0; $i<100000; $i++) { print "AB04\n" };
])
AT_CHECK([$PERL make-big-input.pl > large.txt])
AT_DATA([examine.sps], [dnl
DATA LIST FILE='large.txt' /S 1-2 (A) X 3 .


AGGREGATE OUTFILE=* /BREAK=X /A=N.


EXAMINE /A BY X.
])
AT_CHECK([pspp -o pspp.csv examine.sps])
dnl Ignore output -- this is just a no-crash check.
AT_DATA([more-big-input.pl], 
  [for ($i=0; $i<25000; $i++) { print "AB04\nAB12\n" };
])
AT_CHECK([$PERL more-big-input.pl >> large.txt])
AT_CHECK([pspp -o pspp.csv examine.sps])
dnl Ignore output -- this is just a no-crash check.
AT_CLEANUP


dnl Test that the ID command works with non-numberic variables
AT_SETUP([EXAMINE -- non-numeric ID])

AT_DATA([examine-id.sps], [dnl
data list notable list /x * y (a12).
begin data.
1  one
2  two
3  three
4  four
5  five
6  six
7  seven
8  eight
9  nine
10 ten
11 eleven
12 twelve
30 thirty
300 threehundred
end data.

examine x
	/statistics = extreme
	/id = y
	/plot = boxplot
	.
])

AT_CHECK([pspp -O format=csv examine-id.sps], [0], 
[Table: Case Processing Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
x,14,100%,0,0%,14,100%

Table: Extreme Values
,,,y,Value
x,Highest,1,threehundred,300.00
,,2,thirty      ,30.00
,,3,twelve      ,12.00
,,4,eleven      ,11.00
,,5,ten         ,10.00
,Lowest,1,one         ,1.00
,,2,two         ,2.00
,,3,three       ,3.00
,,4,four        ,4.00
,,5,five        ,5.00
])

AT_CLEANUP 

dnl Test for a crash which happened on cleanup from a bad input syntax
AT_SETUP([EXAMINE -- Bad Input])

AT_DATA([examine-bad.sps], [dnl
data list list /h * g *.
begin data.
1 1
2 1
3 1
4 1
5 2
6 2
7 2
8 2
9 2
end data.

EXAMINE 
	/VARIABLES= h
	BY  g
	/STATISTICS = DESCRIPTIVES EXTREME
        /PLOT = lkajsdas
	.
])

AT_CHECK([pspp -o pspp.csv examine-bad.sps], [1], [ignore])

AT_CLEANUP 


dnl Check the MISSING=REPORT option
AT_SETUP([EXAMINE -- MISSING=REPORT])


AT_DATA([examine-report.sps], [dnl
set format = F22.0.
data list list /x * g *.
begin data.
1   1
2   1
3   1
4   1
5   1
6   1
7   1
8   1
9   1
10   2
20   2
30   2
40   2
50   2
60   2
70   2
80   2
90   2
101   9
201   9
301   9
401   9
501   99
601   99
701   99
801   99
901   99
1001  .
2002  .
3003  .
4004  .
end data.

MISSING VALUES g (9, 99, 999).

EXAMINE
        /VARIABLES = x
        BY  g
        /STATISTICS = EXTREME
        /NOTOTAL
        /MISSING = REPORT.
])


AT_CHECK([pspp -O format=csv examine-report.sps], [0], [dnl
Table: Reading free-form data from INLINE.
Variable,Format
x,F8.0
g,F8.0

Table: Case Processing Summary
,,Cases,,,,,
,,Valid,,Missing,,Total,
,g,N,Percent,N,Percent,N,Percent
x,. (missing),4,100%,0,0%,4,100%
,1,9,100%,0,0%,9,100%
,2,9,100%,0,0%,9,100%
,9 (missing),4,100%,0,0%,4,100%
,99 (missing),5,100%,0,0%,5,100%

Table: Extreme Values
,g,,,Case Number,Value
x,. (missing),Highest,1,31,4004
,,,2,30,3003
,,,3,29,2002
,,,4,28,1001
,,,5,0,0
,,Lowest,1,28,1001
,,,2,29,2002
,,,3,30,3003
,,,4,31,4004
,,,5,31,4004
,1,Highest,1,9,9
,,,2,8,8
,,,3,7,7
,,,4,6,6
,,,5,5,5
,,Lowest,1,1,1
,,,2,2,2
,,,3,3,3
,,,4,4,4
,,,5,5,5
,2,Highest,1,18,90
,,,2,17,80
,,,3,16,70
,,,4,15,60
,,,5,14,50
,,Lowest,1,10,10
,,,2,11,20
,,,3,12,30
,,,4,13,40
,,,5,14,50
,9 (missing),Highest,1,22,401
,,,2,21,301
,,,3,20,201
,,,4,19,101
,,,5,0,0
,,Lowest,1,19,101
,,,2,20,201
,,,3,21,301
,,,4,22,401
,,,5,22,401
,99 (missing),Highest,1,27,901
,,,2,26,801
,,,3,25,701
,,,4,24,601
,,,5,23,501
,,Lowest,1,23,501
,,,2,24,601
,,,3,25,701
,,,4,26,801
,,,5,27,901
])


AT_CLEANUP 


dnl Run a test of the basic STATISTICS using a "real"
dnl dataset and comparing with "real" results kindly
dnl provided by Olaf Nöhring
AT_SETUP([EXAMINE -- sample unweighted])

AT_DATA([sample.sps], [dnl
set format = F22.4.
DATA LIST notable LIST /X *
BEGIN DATA.
461.19000000
466.38000000
479.46000000
480.10000000
483.43000000
488.30000000
489.00000000
491.62000000
505.62000000
511.30000000
521.53000000
526.70000000
528.25000000
538.70000000
540.22000000
540.58000000
546.10000000
548.17000000
553.99000000
566.21000000
575.90000000
584.38000000
593.40000000
357.05000000
359.73000000
360.48000000
373.98000000
374.13000000
381.45000000
383.72000000
390.00000000
400.34000000
415.32000000
415.91000000
418.30000000
421.03000000
422.43000000
426.93000000
433.25000000
436.89000000
445.33000000
446.33000000
446.55000000
456.44000000
689.49000000
691.92000000
695.00000000
695.36000000
698.21000000
699.46000000
706.61000000
710.69000000
715.82000000
715.82000000
741.39000000
752.27000000
756.73000000
757.74000000
759.57000000
796.07000000
813.78000000
817.25000000
825.48000000
831.28000000
849.24000000
890.00000000
894.78000000
935.65000000
935.90000000
945.90000000
1012.8600000
1022.6000000
1061.8100000
1063.5000000
1077.2300000
1151.6300000
1355.2800000
598.88000000
606.91000000
621.60000000
624.80000000
636.13000000
637.38000000
640.32000000
649.35000000
656.51000000
662.55000000
664.69000000
106.22000000
132.24000000
174.76000000
204.85000000
264.93000000
264.99000000
269.84000000
325.12000000
331.67000000
337.26000000
347.68000000
354.91000000
END DATA.

EXAMINE
	x
	/STATISTICS=DESCRIPTIVES
	.
])

AT_CHECK([pspp -O format=csv sample.sps], [0], [dnl
Table: Case Processing Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
X,100,100%,0,0%,100,100%

Table: Descriptives
,,,Statistic,Std. Error
X,Mean,,587.6603,23.2665
,95% Confidence Interval for Mean,Lower Bound,541.4946,
,,Upper Bound,633.8260,
,5% Trimmed Mean,,579.7064,
,Median,,547.1350,
,Variance,,54132.8466,
,Std. Deviation,,232.6647,
,Minimum,,106.2200,
,Maximum,,1355.2800,
,Range,,1249.0600,
,Interquartile Range,,293.1575,
,Skewness,,.6331,.2414
,Kurtosis,,.5300,.4783
])

AT_CLEANUP