Table 8.1, page 203. Consumer Expenditure and Money Stock.
get file 'd:p203.sav'. list.
year quarter expendit stock
1952 1 214.60 159.30
1952 2 217.70 161.20
1952 3 219.60 162.80
1952 4 227.20 164.60
1953 1 230.90 165.90
1953 2 233.30 167.90
1953 3 234.10 168.30
1953 4 232.30 169.70
1954 1 233.70 170.50
1954 2 236.50 171.60
1954 3 238.70 173.90
1954 4 243.20 176.10
1955 1 249.40 178.00
1955 2 254.30 179.10
1955 3 260.90 180.20
1955 4 263.30 181.20
1956 1 265.60 181.60
1956 2 268.20 182.50
1956 3 270.40 183.30
1956 4 275.60 184.30
Number of cases read: 20 Number of cases listed: 20
Table 8.2, page 203. Consumer Expenditure is Regressed on Money Stock.
regression /dependent = expendit /method enter = stock /save sresid(sr).
Figure 8.1, page 204. Index plot of the standardized residuals.
compute index = $casenum. exe. tsplot variable = sr /id = index /format reference.
Durbin Watson Statistic, page 205.
regression /statistics outs /dependent = expendit /method enter = stock /residual durbin.
Section 8.4 and 8.5, page 206-209.
The areg command that handles autocorrelation is not available on base
SPSS.
Table 8.4, page 211.
get file 'd:p211.sav'.
list.
h p d
.09 2.20 .04
.09 2.22 .03
.10 2.24 .04
.10 2.27 .04
.10 2.28 .04
.10 2.29 .04
.11 2.29 .05
.11 2.29 .05
.11 2.30 .05
.11 2.30 .05
.11 2.30 .05
.11 2.34 .06
.11 2.39 .05
.12 2.43 .05
.12 2.48 .05
.12 2.53 .06
.12 2.58 .06
.12 2.61 .06
.12 2.63 .05
.13 2.66 .06
.13 2.68 .07
.13 2.71 .06
.13 2.74 .06
.14 2.77 .07
.14 2.79 .07
Number of cases read: 25 Number of cases listed: 25
Table 8.5, page 212. Regression on Housing Starts (H) versus Population (P).
regression /dependent = h /method enter = p /save sresid(sr).
Figure 8.3, page 212. Index plot of residuals from table 8.5.
compute index = $casenum. exe. tsplot variable = sr /id=index /format reference.
Table 8.6, page 213.
regression /dependent = h /method enter = p d /save sresid(sr2).
Figure 8.4, page 213. Index plot of residuals from table 8.6.
tsplot variable = sr2 /id=index /format reference.
For the equation on top of page 214, see the standardized coefficients column
from the regression from Table 8.6.
Table 8.7, page 215. Ski Sales versus PDI.
get file 'd:p217.sav'. regression /dependent = sales /method enter = pdi /residual durbin /save sres /save sresid(sr).
Figure 8.5, page 215. Index plot of residuals differentiating between season.
compute index = $casenum. exe.
formats sr (f8.2) index (f2.0).
GGRAPH /GRAPHDATASET NAME="GraphDataset" VARIABLES= sr index season /GRAPHSPEC SOURCE=INLINE . BEGIN GPL SOURCE: s=userSource( id( "GraphDataset" ) ) DATA: sr=col( source(s), name( "sr" ) ) DATA: index=col( source(s), name( "index" ) ) DATA: season = col( source(s), name( "season" ), unit.category() ) GUIDE: axis( dim( 1 ), label( "index" ) ) GUIDE: axis( dim( 2 ), label( "Residuals" ), start(0.0), delta(.75) ) SCALE: linear( dim( 1 ) ) SCALE: linear( dim( 2 ), min(-1.50), max(1.50) ) ELEMENT: point( position( ( index * sr ) ), shape( season ) ) END GPL.
Table 8.8, page 217. Disposable Income and Ski Sales, and Seasonal variables for years 1964-1973.
list. quarter sales pdi season sr index Q1/64 37.00 109 1 1.05164 1.00 Q2/64 33.50 115 0 -.56792 2.00 Q3/64 30.80 113 0 -1.36335 3.00 Q4/64 37.90 116 1 .87534 4.00 Q1/65 37.40 118 1 .56648 5.00 Q2/65 31.60 120 0 -1.55216 6.00 Q3/65 34.00 122 0 -.86544 7.00 Q4/65 38.10 124 1 .39704 8.00 Q1/66 40.00 126 1 .90737 9.00 Q2/66 35.00 128 0 -.92432 10.00 Q3/66 34.90 130 0 -1.09078 11.00 Q4/66 40.20 132 1 .56917 12.00 Q1/67 41.90 133 1 1.07638 13.00 Q2/67 34.70 135 0 -1.48856 14.00 Q3/67 38.80 138 0 -.30469 15.00 Q4/67 43.70 140 1 1.21173 16.00 Q1/68 44.20 143 1 1.17872 17.00 Q2/68 40.40 147 0 -.36450 18.00 Q3/68 38.40 148 0 -1.10224 19.00 Q4/68 45.40 151 1 1.04776 20.00 Q1/69 44.90 153 1 .74703 21.00 Q2/69 41.60 156 0 -.55906 22.00 Q3/69 44.00 160 0 -.01960 23.00 Q4/69 48.10 163 1 1.15735 24.00 Q1/70 49.70 166 1 1.49628 25.00 Q2/70 43.90 171 0 -.78603 26.00 Q3/70 41.60 174 0 -1.76254 27.00 Q4/70 51.00 175 1 1.33981 28.00 Q1/71 52.00 180 1 1.34764 29.00 Q2/71 46.20 184 0 -.88522 30.00 Q3/71 47.10 187 0 -.78336 31.00 Q4/71 52.70 189 1 .98941 32.00 Q1/72 52.20 191 1 .68540 33.00 Q2/72 47.00 193 0 -1.22901 34.00 Q3/72 47.80 194 0 -1.02404 35.00 Q4/72 52.80 196 1 .55547 36.00 Q1/73 54.10 199 1 .80119 37.00 Q2/73 49.50 201 0 -.92441 38.00 Q3/73 49.50 202 0 -.99426 39.00 Q4/73 54.30 204 1 .53260 40.00 Number of cases read: 40 Number of cases listed: 40
Table 8.9, page 217. Ski Sales versus PDI and Seasonal Variables.
regression /dependent = sales /method enter = pdi season /residual durbin /save sresid(sr2).
Figure 8.7, page 218.
formats sr2 (f8.2).
GGRAPH /GRAPHDATASET NAME="GraphDataset" VARIABLES= sr2 index season /GRAPHSPEC SOURCE=INLINE . BEGIN GPL SOURCE: s=userSource( id( "GraphDataset" ) ) DATA: sr2=col( source(s), name( "sr2" ) ) DATA: index=col( source(s), name( "index" ) ) DATA: season = col( source(s), name( "season" ), unit.category() ) GUIDE: axis( dim( 1 ), label( "index" ), start(0.0), delta(10) ) GUIDE: axis( dim( 2 ), label( "Residuals" ), start(0.0), delta(1.25) ) SCALE: linear( dim( 1 ), min(0), max(40) ) SCALE: linear( dim( 2 ), min(-2.50), max(2.50) ) ELEMENT: point( position( ( index * sr2 ) ), shape( season ) ) END GPL.
