| blob | d194d73bfb99e69b2f7a811d89b064f227e4a3fe |
1 AT_BANNER([LINEAR REGRESSION])
3 AT_SETUP([LINEAR REGRESSION - basic])
4 AT_DATA([regression.sps], [dnl
5 set format = F22.3.
6 data list notable list / v0 to v2.
7 begin data
8 0.65377128 7.735648 -23.97588
9 -0.13087553 6.142625 -19.63854
10 0.34880368 7.651430 -25.26557
11 0.69249021 6.125125 -16.57090
12 -0.07368178 8.245789 -25.80001
13 -0.34404919 6.031540 -17.56743
14 0.75981559 9.832291 -28.35977
15 -0.46958313 5.343832 -16.79548
16 -0.06108490 8.838262 -29.25689
17 0.56154863 6.200189 -18.58219
18 end data
19 regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=pred resid.
20 list.
21 ])
23 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
24 Table: Model Summary (v2)
25 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
26 ,.971,.942,.925,1.337
28 Table: ANOVA (v2)
29 ,,Sum of Squares,df,Mean Square,F,Sig.
30 ,Regression,202.753,2,101.376,56.754,.000
31 ,Residual,12.504,7,1.786,,
32 ,Total,215.256,9,,,
34 Table: Coefficients (v2)
35 ,,Unstandardized Coefficients,,Standardized Coefficients,,
36 ,,B,Std. Error,Beta,t,Sig.
37 ,(Constant),2.191,2.357,.000,.930,.380
38 ,v0,1.813,1.053,.171,1.722,.129
39 ,v1,-3.427,.332,-1.026,-10.334,.000
41 Table: Data List
42 v0,v1,v2,RES1,PRED1
43 .654,7.736,-23.976,-.84,-23.13
44 -.131,6.143,-19.639,-.54,-19.10
45 .349,7.651,-25.266,-1.87,-23.40
46 .692,6.125,-16.571,.97,-17.54
47 -.074,8.246,-25.800,.40,-26.20
48 -.344,6.032,-17.567,1.53,-19.10
49 .760,9.832,-28.360,1.77,-30.13
50 -.470,5.344,-16.795,.18,-16.97
51 -.061,8.838,-29.257,-1.05,-28.21
52 .562,6.200,-18.582,-.54,-18.04
53 ])
54 AT_CLEANUP
57 # Test to ensure that the /SAVE subcommand works properly when SPLIT is active
58 AT_SETUP([LINEAR REGRESSION - SAVE vs SPLITS])
60 # Generate some test data based on a linear model
61 AT_DATA([gen-data.sps], [dnl
62 set seed = 1.
63 input program.
64 loop #c = 1 to 20.
65 compute x0 = rv.normal (0,1).
66 compute x1 = rv.normal (0,2).
67 compute err = rv.normal (0,0.1).
68 compute y = 4 - 2 * x0 + 3 * x1 + err.
69 compute g = (#c > 10).
70 end case.
71 end loop.
72 end file.
73 end input program.
75 print outfile='regdata.txt' /g x0 x1 y err *.
76 execute.
77 ])
79 AT_CHECK([pspp -O format=csv gen-data.sps], [0], [ignore])
81 # Use our test data to create a predictor and a residual variable
82 # for G == 0
83 AT_DATA([regression0.sps], [dnl
84 data list notable file='regdata.txt' list /g x0 x1 y err *.
86 select if (g = 0).
88 regression
89 /variables = x0 x1
90 /dependent = y
91 /statistics = all
92 /save = pred resid.
93 .
95 print outfile='outdata-g0.txt' /g x0 x1 y err res1 pred1 *.
96 execute.
97 ])
100 AT_CHECK([pspp -O format=csv regression0.sps], [0], [ignore])
102 # Use our test data to create a predictor and a residual variable
103 # for G == 1
104 AT_DATA([regression1.sps], [dnl
105 data list notable file='regdata.txt' list /g x0 x1 y err *.
107 select if (g = 1).
109 regression
110 /variables = x0 x1
111 /dependent = y
112 /statistics = all
113 /save = pred resid.
114 .
116 print outfile='outdata-g1.txt' /g x0 x1 y err res1 pred1 *.
117 execute.
118 ])
121 AT_CHECK([pspp -O format=csv regression1.sps], [0], [ignore])
123 # Use our test data to create a predictor and a residual variable
124 # The data is split on G
125 AT_DATA([regression-split.sps], [dnl
126 data list notable file='regdata.txt' list /g x0 x1 y err *.
128 split file by g.
130 regression
131 /variables = x0 x1
132 /dependent = y
133 /statistics = all
134 /save = pred resid.
135 .
137 print outfile='outdata-split.txt' /g x0 x1 y err res1 pred1 *.
138 execute.
139 ])
141 AT_CHECK([pspp -O format=csv regression-split.sps], [0], [ignore])
143 # The concatenation of G==0 and G==1 should be identical to the SPLIT data
144 AT_CHECK([cat outdata-g0.txt outdata-g1.txt | diff outdata-split.txt - ], [0], [])
146 AT_CLEANUP
149 # Test that the procedure behaves sensibly when presented with
150 # multiple dependent variables
151 AT_SETUP([LINEAR REGRESSION multiple dependent variables])
152 AT_DATA([regression.sps], [dnl
153 set seed = 2.
154 input program.
155 loop #c = 1 to 200.
156 compute x0 = rv.normal (0, 1).
157 compute x1 = rv.normal (0, 2).
158 compute err = rv.normal (0, 0.8).
159 compute y = 2 - 1.5 * x0 + 8.4 * x1 + err.
160 compute ycopy = y.
161 end case.
162 end loop.
163 end file.
164 end input program.
166 regression
167 /variables = x0 x1
168 /dependent = y ycopy
169 /statistics = default.
170 ])
172 AT_CHECK([pspp -O format=csv regression.sps > output], [0], [ignore])
174 AT_CHECK([head -16 output > first], [0], [])
175 AT_CHECK([tail -16 output > second], [0], [])
177 AT_CHECK([sed -e 's/ycopy/y/g' second | diff first -], [0], [])
180 AT_CLEANUP
182 # Tests the QR decomposition used by the REGRESSION command.
183 AT_SETUP([LINEAR REGRESSION test of QR decomposition])
184 AT_DATA([regression.sps], [dnl
185 data list list / v0 to v1.
186 begin data
187 -12.84099361 0.873270778
188 16.64932538 0.371315664
189 -1.88061907 0.505503722
190 -6.20952354 0.734698282
191 0.33272576 0.891224610
192 -5.54912717 0.052318165
193 6.11832417 0.448853404
194 11.78124974 0.470447593
195 0.75960353 0.565082303
196 6.06432768 0.149316743
197 -2.64919436 0.752532411
198 -10.32250712 0.798263603
199 2.06355038 0.469129797
200 -9.71851742 0.927162270
201 4.65582553 0.250629262
202 9.54574474 0.847032310
203 7.35544368 0.197028541
204 -2.09609740 0.400584261
205 10.30101161 0.671546480
206 -5.24501039 0.929962876
207 1.73412473 0.758161354
208 -3.12732732 0.569785505
209 12.66261501 0.630640223
210 -2.90956805 0.576067804
211 4.89649177 0.624483995
212 13.64613114 0.591089881
213 14.03198397 0.544587572
214 2.23566810 0.967898139
215 5.37367760 0.916246929
216 9.01346888 0.451702743
217 0.75378683 0.235544137
218 -3.47470624 0.742668194
219 -1.02063266 0.860311687
220 -2.67132813 0.082460702
221 23.67661680 0.932553932
222 7.95061359 0.430161125
223 2.05300558 0.066331375
224 -2.01332644 0.163705417
225 20.00663784 0.587292630
226 3.06099417 0.161411889
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228 -6.85287183 0.548714855
229 -4.27923809 0.630997663
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232 -12.80962955 0.886070341
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243 7.02816784 0.042277017
244 -21.20245068 0.430673493
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248 3.84286316 0.685105924
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251 10.86673874 0.518530912
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264 8.55606848 0.373011464
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268 1.55798880 0.822587656
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317 1.37952764 0.899991932
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1652 7.88002491 0.990156110
1653 10.27680283 0.251087079
1654 -9.42498970 0.292462244
1655 6.73027640 0.213065205
1656 1.28169895 0.353152789
1657 -14.29203733 0.264563048
1658 20.35772711 0.265208837
1659 3.55095071 0.242905653
1660 -17.97067670 0.373951756
1661 10.53141139 0.247520698
1662 0.05293205 0.579940423
1663 12.79674707 0.288031751
1664 -5.44235185 0.075899079
1665 14.29464811 0.960707538
1666 -1.36753291 0.124265178
1667 -4.25946974 0.521720352
1668 -12.46519252 0.385503339
1669 -6.65343143 0.540942219
1670 5.55949184 0.143194404
1671 -1.20480594 0.515905644
1672 -4.13839908 0.164461445
1673 -2.21345425 0.812969725
1674 3.94223380 0.229238952
1675 -10.78661097 0.395049514
1676 3.06997341 0.791234255
1677 24.82205477 0.110859039
1678 6.28791249 0.867125744
1679 -2.80296119 0.703583849
1680 13.24274039 0.425951975
1681 -0.19577471 0.361568727
1682 -2.34894781 0.954814545
1683 19.76339577 0.635462177
1684 -1.87591480 0.149121567
1685 -7.70962391 0.711708342
1686 -2.46291902 0.390902746
1687 end data
1688 regression /variables=v0 v1 /statistics defaults /dependent=v0 /method=enter.
1689 ])
1691 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
1692 Table: Reading free-form data from INLINE.
1693 Variable,Format
1694 v0,F8.0
1695 v1,F8.0
1697 Table: Model Summary (v0)
1698 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
1699 ,.05,.00,.00,8.11
1701 Table: ANOVA (v0)
1702 ,,Sum of Squares,df,Mean Square,F,Sig.
1703 ,Regression,235.23,1,235.23,3.58,.059
1704 ,Residual,98438.40,1498,65.71,,
1705 ,Total,98673.63,1499,,,
1707 Table: Coefficients (v0)
1708 ,,Unstandardized Coefficients,,Standardized Coefficients,,
1709 ,,B,Std. Error,Beta,t,Sig.
1710 ,(Constant),1.24,.42,.00,2.95,.003
1711 ,v1,1.37,.72,.05,1.89,.059
1712 ])
1714 AT_CLEANUP
1716 AT_SETUP([LINEAR REGRESSION no crash on all missing])
1717 AT_DATA([regcrash.sps], [dnl
1718 data list list /x * y.
1719 begin data.
1720 . .
1721 . .
1722 . .
1723 . .
1724 . .
1725 . .
1726 . .
1727 . .
1728 . .
1729 . .
1730 end data.
1733 regression /variables=x y /dependent=y.
1734 ])
1736 AT_CHECK([pspp -o pspp.csv regcrash.sps], [1], [ignore], [ignore])
1738 AT_CLEANUP
1742 AT_SETUP([LINEAR REGRESSION missing dependent variable])
1744 dnl Test for a bug where missing values in the dependent variable were not being
1745 dnl ignored like they should have been.
1746 AT_DATA([reg-mdv-ref.sps], [dnl
1747 data list notable list / v0 to v2.
1748 begin data
1749 0.65377128 7.735648 -23.97588
1750 -0.13087553 6.142625 -19.63854
1751 0.34880368 7.651430 -25.26557
1752 0.69249021 6.125125 -16.57090
1753 -0.07368178 8.245789 -25.80001
1754 -0.34404919 6.031540 -17.56743
1755 0.75981559 9.832291 -28.35977
1756 -0.46958313 5.343832 -16.79548
1757 -0.06108490 8.838262 -29.25689
1758 0.56154863 6.200189 -18.58219
1759 end data
1760 regression /variables=v0 v1
1761 /statistics defaults
1762 /dependent=v2
1763 /method=enter.
1764 ])
1766 AT_CHECK([pspp -o pspp-ref.csv reg-mdv-ref.sps])
1768 AT_DATA([reg-mdv.sps], [dnl
1769 data list notable list / v0 to v2.
1770 begin data
1771 0.65377128 7.735648 -23.97588
1772 -0.13087553 6.142625 -19.63854
1773 0.34880368 7.651430 -25.26557
1774 0.69249021 6.125125 -16.57090
1775 -0.07368178 8.245789 -25.80001
1776 -0.34404919 6.031540 -17.56743
1777 0.75981559 9.832291 -28.35977
1778 -0.46958313 5.343832 -16.79548
1779 -0.06108490 8.838262 -29.25689
1780 0.56154863 6.200189 -18.58219
1781 0.5 8 9
1782 end data
1784 missing values v2 (9).
1786 regression /variables=v0 v1
1787 /statistics defaults
1788 /dependent=v2
1789 /method=enter.
1790 ])
1792 AT_CHECK([pspp -o pspp.csv reg-mdv.sps])
1794 AT_CHECK([diff pspp.csv pspp-ref.csv])
1797 AT_CLEANUP
1799 AT_SETUP([LINEAR REGRESSION with invalid syntax (and empty dataset)])
1801 AT_DATA([ss.sps], [dnl
1802 data list notable list / v0 to v2.
1803 begin data
1804 end data.
1806 regression /variables=v0 v1
1807 /statistics r coeff anova
1808 /dependent=v2
1809 /method=enter v2.
1810 ])
1812 AT_CHECK([pspp ss.sps], [1], [ignore])
1814 AT_CLEANUP
1817 dnl The following example comes from
1818 dnl http://www.ats.ucla.edu/stat/spss/output/reg_spss%28long%29.htm
1819 AT_SETUP([LINEAR REGRESSION coefficient confidence interval])
1821 AT_DATA([conf.sps], [dnl
1822 set format = F22.3.
1824 data list notable list /math female socst read science *
1825 begin data.
1826 41.00 .00 57.00 57.00 47.00
1827 53.00 1.00 61.00 68.00 63.00
1828 54.00 .00 31.00 44.00 58.00
1829 47.00 .00 56.00 63.00 53.00
1830 57.00 .00 61.00 47.00 53.00
1831 51.00 .00 61.00 44.00 63.00
1832 42.00 .00 61.00 50.00 53.00
1833 45.00 .00 36.00 34.00 39.00
1834 54.00 .00 51.00 63.00 58.00
1835 52.00 .00 51.00 57.00 50.00
1836 51.00 .00 61.00 60.00 53.00
1837 51.00 .00 61.00 57.00 63.00
1838 71.00 .00 71.00 73.00 61.00
1839 57.00 .00 46.00 54.00 55.00
1840 50.00 .00 56.00 45.00 31.00
1841 43.00 .00 56.00 42.00 50.00
1842 51.00 .00 56.00 47.00 50.00
1843 60.00 .00 56.00 57.00 58.00
1844 62.00 .00 61.00 68.00 55.00
1845 57.00 .00 46.00 55.00 53.00
1846 35.00 .00 41.00 63.00 66.00
1847 75.00 .00 66.00 63.00 72.00
1848 45.00 .00 56.00 50.00 55.00
1849 57.00 .00 61.00 60.00 61.00
1850 45.00 .00 46.00 37.00 39.00
1851 46.00 .00 31.00 34.00 39.00
1852 66.00 .00 66.00 65.00 61.00
1853 57.00 .00 46.00 47.00 58.00
1854 49.00 .00 46.00 44.00 39.00
1855 49.00 .00 41.00 52.00 55.00
1856 57.00 .00 51.00 42.00 47.00
1857 64.00 .00 61.00 76.00 64.00
1858 63.00 .00 71.00 65.00 66.00
1859 57.00 .00 31.00 42.00 72.00
1860 50.00 .00 61.00 52.00 61.00
1861 58.00 .00 66.00 60.00 61.00
1862 75.00 .00 66.00 68.00 66.00
1863 68.00 .00 66.00 65.00 66.00
1864 44.00 .00 36.00 47.00 36.00
1865 40.00 .00 51.00 39.00 39.00
1866 41.00 .00 51.00 47.00 42.00
1867 62.00 .00 51.00 55.00 58.00
1868 57.00 .00 51.00 52.00 55.00
1869 43.00 .00 41.00 42.00 50.00
1870 48.00 .00 66.00 65.00 63.00
1871 63.00 .00 46.00 55.00 69.00
1872 39.00 .00 47.00 50.00 49.00
1873 70.00 .00 51.00 65.00 63.00
1874 63.00 .00 46.00 47.00 53.00
1875 59.00 .00 51.00 57.00 47.00
1876 61.00 .00 56.00 53.00 57.00
1877 38.00 .00 41.00 39.00 47.00
1878 61.00 .00 46.00 44.00 50.00
1879 49.00 .00 71.00 63.00 55.00
1880 73.00 .00 66.00 73.00 69.00
1881 44.00 .00 42.00 39.00 26.00
1882 42.00 .00 32.00 37.00 33.00
1883 39.00 .00 46.00 42.00 56.00
1884 55.00 .00 41.00 63.00 58.00
1885 52.00 .00 51.00 48.00 44.00
1886 45.00 .00 61.00 50.00 58.00
1887 61.00 .00 66.00 47.00 69.00
1888 39.00 .00 46.00 44.00 34.00
1889 41.00 .00 36.00 34.00 36.00
1890 50.00 .00 61.00 50.00 36.00
1891 40.00 .00 26.00 44.00 50.00
1892 60.00 .00 66.00 60.00 55.00
1893 47.00 .00 26.00 47.00 42.00
1894 59.00 .00 44.00 63.00 65.00
1895 49.00 .00 36.00 50.00 44.00
1896 46.00 .00 51.00 44.00 39.00
1897 58.00 .00 61.00 60.00 58.00
1898 71.00 .00 66.00 73.00 63.00
1899 58.00 .00 66.00 68.00 74.00
1900 46.00 .00 51.00 55.00 58.00
1901 43.00 .00 31.00 47.00 45.00
1902 54.00 .00 61.00 55.00 49.00
1903 56.00 .00 66.00 68.00 63.00
1904 46.00 .00 46.00 31.00 39.00
1905 54.00 .00 56.00 47.00 42.00
1906 57.00 .00 56.00 63.00 55.00
1907 54.00 .00 36.00 36.00 61.00
1908 71.00 .00 56.00 68.00 66.00
1909 48.00 .00 56.00 63.00 63.00
1910 40.00 .00 41.00 55.00 44.00
1911 64.00 .00 66.00 55.00 63.00
1912 51.00 .00 56.00 52.00 53.00
1913 39.00 .00 56.00 34.00 42.00
1914 40.00 .00 31.00 50.00 34.00
1915 61.00 .00 56.00 55.00 61.00
1916 66.00 .00 46.00 52.00 47.00
1917 49.00 .00 46.00 63.00 66.00
1918 65.00 1.00 61.00 68.00 69.00
1919 52.00 1.00 48.00 39.00 44.00
1920 46.00 1.00 51.00 44.00 47.00
1921 61.00 1.00 51.00 50.00 63.00
1922 72.00 1.00 56.00 71.00 66.00
1923 71.00 1.00 71.00 63.00 69.00
1924 40.00 1.00 41.00 34.00 39.00
1925 69.00 1.00 61.00 63.00 61.00
1926 64.00 1.00 66.00 68.00 69.00
1927 56.00 1.00 61.00 47.00 66.00
1928 49.00 1.00 41.00 47.00 33.00
1929 54.00 1.00 51.00 63.00 50.00
1930 53.00 1.00 51.00 52.00 61.00
1931 66.00 1.00 56.00 55.00 42.00
1932 67.00 1.00 56.00 60.00 50.00
1933 40.00 1.00 33.00 35.00 51.00
1934 46.00 1.00 56.00 47.00 50.00
1935 69.00 1.00 71.00 71.00 58.00
1936 40.00 1.00 56.00 57.00 61.00
1937 41.00 1.00 51.00 44.00 39.00
1938 57.00 1.00 66.00 65.00 46.00
1939 58.00 1.00 56.00 68.00 59.00
1940 57.00 1.00 66.00 73.00 55.00
1941 37.00 1.00 41.00 36.00 42.00
1942 55.00 1.00 46.00 43.00 55.00
1943 62.00 1.00 66.00 73.00 58.00
1944 64.00 1.00 56.00 52.00 58.00
1945 40.00 1.00 51.00 41.00 39.00
1946 50.00 1.00 51.00 60.00 50.00
1947 46.00 1.00 56.00 50.00 50.00
1948 53.00 1.00 56.00 50.00 39.00
1949 52.00 1.00 46.00 47.00 48.00
1950 45.00 1.00 46.00 47.00 34.00
1951 56.00 1.00 61.00 55.00 58.00
1952 45.00 1.00 56.00 50.00 44.00
1953 54.00 1.00 41.00 39.00 50.00
1954 56.00 1.00 46.00 50.00 47.00
1955 41.00 1.00 26.00 34.00 29.00
1956 54.00 1.00 56.00 57.00 50.00
1957 72.00 1.00 56.00 57.00 54.00
1958 56.00 1.00 51.00 68.00 50.00
1959 47.00 1.00 46.00 42.00 47.00
1960 49.00 1.00 66.00 61.00 44.00
1961 60.00 1.00 66.00 76.00 67.00
1962 54.00 1.00 46.00 47.00 58.00
1963 55.00 1.00 56.00 46.00 44.00
1964 33.00 1.00 41.00 39.00 42.00
1965 49.00 1.00 61.00 52.00 44.00
1966 43.00 1.00 51.00 28.00 44.00
1967 50.00 1.00 52.00 42.00 50.00
1968 52.00 1.00 51.00 47.00 39.00
1969 48.00 1.00 41.00 47.00 44.00
1970 58.00 1.00 66.00 52.00 53.00
1971 43.00 1.00 61.00 47.00 48.00
1972 41.00 1.00 31.00 50.00 55.00
1973 43.00 1.00 51.00 44.00 44.00
1974 46.00 1.00 41.00 47.00 40.00
1975 44.00 1.00 41.00 45.00 34.00
1976 43.00 1.00 46.00 47.00 42.00
1977 61.00 1.00 56.00 65.00 58.00
1978 40.00 1.00 51.00 43.00 50.00
1979 49.00 1.00 61.00 47.00 53.00
1980 56.00 1.00 66.00 57.00 58.00
1981 61.00 1.00 71.00 68.00 55.00
1982 50.00 1.00 61.00 52.00 54.00
1983 51.00 1.00 61.00 42.00 47.00
1984 42.00 1.00 41.00 42.00 42.00
1985 67.00 1.00 66.00 66.00 61.00
1986 53.00 1.00 61.00 47.00 53.00
1987 50.00 1.00 58.00 57.00 51.00
1988 51.00 1.00 31.00 47.00 63.00
1989 72.00 1.00 61.00 57.00 61.00
1990 48.00 1.00 61.00 52.00 55.00
1991 40.00 1.00 31.00 44.00 40.00
1992 53.00 1.00 61.00 50.00 61.00
1993 39.00 1.00 36.00 39.00 47.00
1994 63.00 1.00 41.00 57.00 55.00
1995 51.00 1.00 37.00 57.00 53.00
1996 45.00 1.00 43.00 42.00 50.00
1997 39.00 1.00 61.00 47.00 47.00
1998 42.00 1.00 39.00 42.00 31.00
1999 62.00 1.00 51.00 60.00 61.00
2000 44.00 1.00 51.00 44.00 35.00
2001 65.00 1.00 66.00 63.00 54.00
2002 63.00 1.00 71.00 65.00 55.00
2003 54.00 1.00 41.00 39.00 53.00
2004 45.00 1.00 36.00 50.00 58.00
2005 60.00 1.00 51.00 52.00 56.00
2006 49.00 1.00 51.00 60.00 50.00
2007 48.00 1.00 51.00 44.00 39.00
2008 57.00 1.00 61.00 52.00 63.00
2009 55.00 1.00 61.00 55.00 50.00
2010 66.00 1.00 56.00 50.00 66.00
2011 64.00 1.00 71.00 65.00 58.00
2012 55.00 1.00 51.00 52.00 53.00
2013 42.00 1.00 36.00 47.00 42.00
2014 56.00 1.00 61.00 63.00 55.00
2015 53.00 1.00 66.00 50.00 53.00
2016 41.00 1.00 41.00 42.00 42.00
2017 42.00 1.00 41.00 36.00 50.00
2018 53.00 1.00 56.00 50.00 55.00
2019 42.00 1.00 51.00 41.00 34.00
2020 60.00 1.00 56.00 47.00 50.00
2021 52.00 1.00 56.00 55.00 42.00
2022 38.00 1.00 46.00 42.00 36.00
2023 57.00 1.00 52.00 57.00 55.00
2024 58.00 1.00 61.00 55.00 58.00
2025 65.00 1.00 61.00 63.00 53.00
2026 end data.
2028 regression
2029 /variables = math female socst read
2030 /statistics = coeff r anova ci (95)
2031 /dependent = science
2032 /method = enter
2033 ])
2035 AT_CHECK([pspp -O format=csv conf.sps], [0], [dnl
2036 Table: Model Summary (science)
2037 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
2038 ,.699,.489,.479,7.148
2040 Table: ANOVA (science)
2041 ,,Sum of Squares,df,Mean Square,F,Sig.
2042 ,Regression,9543.721,4,2385.930,46.695,.000
2043 ,Residual,9963.779,195,51.096,,
2044 ,Total,19507.500,199,,,
2046 Table: Coefficients (science)
2047 ,,Unstandardized Coefficients,,Standardized Coefficients,,,95% Confidence Interval for B,
2048 ,,B,Std. Error,Beta,t,Sig.,Lower Bound,Upper Bound
2049 ,(Constant),12.325,3.194,.000,3.859,.000,6.027,18.624
2050 ,math,.389,.074,.368,5.252,.000,.243,.535
2051 ,female,-2.010,1.023,-.101,-1.965,.051,-4.027,.007
2052 ,socst,.050,.062,.054,.801,.424,-.073,.173
2053 ,read,.335,.073,.347,4.607,.000,.192,.479
2054 ])
2057 AT_CLEANUP