Use greater-than-or-equal to sign instead of '>='.
[pspp-builds.git] / tests / language / dictionary / weight.at
1 AT_BANNER([WEIGHT])
2
3 AT_SETUP([WEIGHT])
4 AT_DATA([weight.txt], [dnl
5    18    1
6    19    7
7    20   26
8    21   76
9    22   57
10    23   58
11    24   38
12    25   38
13    26   30
14    27   21
15    28   23
16    29   24
17    30   23
18    31   14
19    32   21
20    33   21
21    34   14
22    35   14
23    36   17
24    37   11
25    38   16
26    39   14
27    40   15
28    41   14
29    42   14
30    43    8
31    44   15
32    45   10
33    46   12
34    47   13
35    48   13
36    49    5
37    50    5
38    51    3
39    52    7
40    53    6
41    54    2
42    55    2
43    56    2
44    57    3
45    58    1
46    59    3
47    61    1
48    62    3
49    63    1
50    64    1
51    65    2
52    70    1
53    78    1
54    79    1
55    80    1
56    94    1
57 ])
58 AT_DATA([weight.sps], [dnl
59 SET FORMAT F8.3.
60 data list file='weight.txt'/AVAR 1-5 BVAR 6-10.
61 weight by BVAR.
62
63 descriptives AVAR /statistics all /format serial.
64 frequencies AVAR /statistics all.
65 ])
66 AT_CHECK([pspp -o pspp.csv weight.sps])
67 AT_CHECK([cat pspp.csv], [0], [dnl
68 Table: Reading 1 record from `weight.txt'.
69 Variable,Record,Columns,Format
70 AVAR,1,1-  5,F5.0
71 BVAR,1,6- 10,F5.0
72
73 Table: Valid cases = 730; cases with missing value(s) = 0.
74 Variable,Valid N,Missing N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
75 AVAR,730,0,31.515,.405,10.937,119.608,2.411,.181,1.345,.090,76.000,18.000,94.000,23006.00
76
77 Table: AVAR
78 Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
79 ,18,1,.137,.137,.137
80 ,19,7,.959,.959,1.096
81 ,20,26,3.562,3.562,4.658
82 ,21,76,10.411,10.411,15.068
83 ,22,57,7.808,7.808,22.877
84 ,23,58,7.945,7.945,30.822
85 ,24,38,5.205,5.205,36.027
86 ,25,38,5.205,5.205,41.233
87 ,26,30,4.110,4.110,45.342
88 ,27,21,2.877,2.877,48.219
89 ,28,23,3.151,3.151,51.370
90 ,29,24,3.288,3.288,54.658
91 ,30,23,3.151,3.151,57.808
92 ,31,14,1.918,1.918,59.726
93 ,32,21,2.877,2.877,62.603
94 ,33,21,2.877,2.877,65.479
95 ,34,14,1.918,1.918,67.397
96 ,35,14,1.918,1.918,69.315
97 ,36,17,2.329,2.329,71.644
98 ,37,11,1.507,1.507,73.151
99 ,38,16,2.192,2.192,75.342
100 ,39,14,1.918,1.918,77.260
101 ,40,15,2.055,2.055,79.315
102 ,41,14,1.918,1.918,81.233
103 ,42,14,1.918,1.918,83.151
104 ,43,8,1.096,1.096,84.247
105 ,44,15,2.055,2.055,86.301
106 ,45,10,1.370,1.370,87.671
107 ,46,12,1.644,1.644,89.315
108 ,47,13,1.781,1.781,91.096
109 ,48,13,1.781,1.781,92.877
110 ,49,5,.685,.685,93.562
111 ,50,5,.685,.685,94.247
112 ,51,3,.411,.411,94.658
113 ,52,7,.959,.959,95.616
114 ,53,6,.822,.822,96.438
115 ,54,2,.274,.274,96.712
116 ,55,2,.274,.274,96.986
117 ,56,2,.274,.274,97.260
118 ,57,3,.411,.411,97.671
119 ,58,1,.137,.137,97.808
120 ,59,3,.411,.411,98.219
121 ,61,1,.137,.137,98.356
122 ,62,3,.411,.411,98.767
123 ,63,1,.137,.137,98.904
124 ,64,1,.137,.137,99.041
125 ,65,2,.274,.274,99.315
126 ,70,1,.137,.137,99.452
127 ,78,1,.137,.137,99.589
128 ,79,1,.137,.137,99.726
129 ,80,1,.137,.137,99.863
130 ,94,1,.137,.137,100.000
131 Total,,730,100.0,100.0,
132
133 Table: AVAR
134 N,Valid,730
135 ,Missing,0
136 Mean,,31.515
137 S.E. Mean,,.405
138 Mode,,21.000
139 Std Dev,,10.937
140 Variance,,119.608
141 Kurtosis,,2.411
142 S.E. Kurt,,.181
143 Skewness,,1.345
144 S.E. Skew,,.090
145 Range,,76.000
146 Minimum,,18.000
147 Maximum,,94.000
148 Sum,,23006.00
149 Percentiles,50 (Median),28
150 ])
151 AT_CLEANUP