UCLA Academic Technology Services HomeServicesClassesContactJobs
Search

SPSS Textbook Examples
Regression Analysis by Example, Third Edition
Chapter 3:  Multiple Linear Regression

Table 3.3, Page 54: Supervisor Performance Data

get file 'D:\p054.sav'.
list.
       y       x1       x2       x3       x4       x5       x6

      43       51       30       39       61       92       45
      63       64       51       54       63       73       47
      71       70       68       69       76       86       48
      61       63       45       47       54       84       35
      81       78       56       66       71       83       47
      43       55       49       44       54       49       34
      58       67       42       56       66       68       35
      71       75       50       55       70       66       41
      72       82       72       67       71       83       31
      67       61       45       47       62       80       41
      64       53       53       58       58       67       34
      67       60       47       39       59       74       41
      69       62       57       42       55       63       25
      68       83       83       45       59       77       35
      77       77       54       72       79       77       46
      81       90       50       72       60       54       36
      74       85       64       69       79       79       63
      65       60       65       75       55       80       60
      65       70       46       57       75       85       46
      50       58       68       54       64       78       52
      50       40       33       34       43       64       33
      64       61       52       62       66       80       41
      53       66       52       50       63       80       37
      40       37       42       58       50       57       49
      63       54       42       48       66       75       33
      66       77       66       63       88       76       72
      78       75       58       74       80       78       49
      48       57       44       45       51       83       38
      85       85       71       71       77       74       55
      82       82       39       59       64       78       39

Number of cases read:  30    Number of cases listed:  30

Regression coefficients for page 57, equation (3.12)

regression 
 /dependent = y 
 /method = enter  x1 x2.

Regression coefficients for page 57, equation (3.13)

regression 
 /dependent = y
 /method = enter x1
 /save resid (eyex1).

Regression coefficients for page 57, equation (3.14)

regression 
 /dependent = x2
 /method = enter x1
 /save resid (ex2ex1).

Table 3.4, Page 58, Partial Residuals

list eyex1 ex2ex1.
      eyex1      ex2ex1

   -9.86142   -15.13003
     .32865     -.79945
    3.80099    13.12236
    -.91674    -6.28642
    7.76411    -2.98190
  -12.87986     1.81784
   -6.93518   -11.33855
     .02794    -7.44280
   -4.25432    10.96597
    6.59248    -5.26035
    9.62936     6.84390
    7.34709    -2.74732
    7.83787     6.22661
   -9.00893    21.45294
    4.51872    -4.46887
   -1.29120   -15.13828
   -4.51815     1.42688
    5.34709    15.25268
   -2.19901    -8.87764
   -8.14369    19.27874
    5.43929    -6.48668
    3.59248     1.73965
  -11.18057     -.82551
   -2.29688     4.05241
    7.87475    -4.66913
   -6.48128     7.53113
    7.02794      .55720
   -9.38908    -4.20823
    6.48185     8.42688
    5.74568   -22.03403

Number of cases read:  30    Number of cases listed:  30

Regression coefficients for page 58, equation (3.15)

regression 
 /dependent = eyex1
 /method = enter ex2ex1.

Table 3.5, page 63. Regression Output for the Supervisor Performance Data

regression 
 /dependent = y
 /method = enter x1 x2 x3 x4 x5 x6.

Hypothesis test for equations (3.36) and (3.37), and Table 3.7, page 67

regression
 /dependent = y
 /method = test(x1 x2 x3 x4 x5 x6).

Hypothesis test for equation (3.39) and Table 3.8, Page 69

regression
 /dependent = y
 /method = enter x1 x3
 /method = test(x2 x4 x5 x6).

F-ratio test in middle of page 71, test whether x1=x3
NOTE:  SPSS does not allow direct testing for equal slopes, therefore we have to use an incremental F-test using equation (3.48) and evaluate it using the equation in the middle of page 71.

compute w = x1 + x3.
exe.
regression
 /dependent = y
 /method = enter w.

regression
/dependent = y
/method = enter x1 x3.

NOTE:  F for x1=x3: [((.708-.669)/(2.1))/((1-.708)(30-2-1)) = 3.65.

Estimating and Testing of Regression Parameters under constraints, page 72-73

compute yprime = y - x3.
compute v = x1-x3.
exe.
regression
 /dependent = yprime
 /method enter = v.

NOTE:  The regression coefficient for x3 is 1 - v = .306.


How to cite this page

Report an error on this page

UCLA Researchers are invited to our Statistical Consulting Services
We recommend others to our list of Other Resources for Statistical Computing Help
These pages are Copyrighted (c) by UCLA Academic Technology Services


The content of this web site should not be construed as an endorsement of any particular web site, book, or software product by the University of California