 MTB > let c4 = c3/c2
 MTB > let c5 = loge(c4/(1 - c4))
 MTB > print c1-c5
 
  ROW    C1     C2     C3      C4        C5
 
    1     5    200     32   0.160  -1.65823
    2    10    200     51   0.255  -1.07212
    3    15    200     70   0.350  -0.61904
    4    20    200    103   0.515   0.06002
    5    30    200    148   0.740   1.04597
 
 MTB > let c6 = c2*c4*(1 - c4)
 MTB > print c1-c6
 
  ROW    C1     C2     C3      C4        C5       C6
 
    1     5    200     32   0.160  -1.65823   26.880
    2    10    200     51   0.255  -1.07212   37.995
    3    15    200     70   0.350  -0.61904   45.500
    4    20    200    103   0.515   0.06002   49.955
    5    30    200    148   0.740   1.04597   38.480
 
 MTB > plot c5 c1 
 
          -
       1.0+                                                       *
          -
  C5      -
          -
          -
       0.0+                                   *
          -
          -
          -                         *
          -
      -1.0+               *
          -
          -
          -     *
          -
      -2.0+
            ----+---------+---------+---------+---------+---------+--C1      
              5.0      10.0      15.0      20.0      25.0      30.0

 MTB > regress c5 1 c1 c11 c12 
 
 The regression equation is
 C5 = - 2.19 + 0.109 C1
 
 Predictor       Coef       Stdev    t-ratio        p
 Constant    -2.18602     0.05722     -38.20    0.000
 C1          0.108584    0.003150      34.47    0.000
 
 s = 0.06059     R-sq = 99.7%     R-sq(adj) = 99.7%
 
 Analysis of Variance
 
 SOURCE       DF          SS          MS         F        p
 Regression    1      4.3624      4.3624   1188.27    0.000
 Error         3      0.0110      0.0037
 Total         4      4.3735
 
 
 
 MTB > regress c5 1 c1 c21 c22;
 SUBC> weights c6.
 
 The regression equation is
 C5 = - 2.19 + 0.109 C1
 
 Predictor       Coef       Stdev    t-ratio        p
 Constant    -2.18506     0.06783     -32.21    0.000
 C1          0.108700    0.003632      29.93    0.000
 
 Analysis of Variance
 
 SOURCE       DF          SS          MS         F        p
 Regression    1      151.98      151.98    895.53    0.000
 Error         3        0.51        0.17
 Total         4      152.49
 
 
 
 MTB > print c1 c4 c12 c22
 
  ROW    C1      C4       C12       C22
 
    1     5   0.160  -1.64310  -1.64156
    2    10   0.255  -1.10018  -1.09806
    3    15   0.350  -0.55726  -0.55455
    4    20   0.515  -0.01435  -0.01105
    5    30   0.740   1.07149   1.07595
 
 MTB > let c13 = expo(c12)/(1 + expo(c12))
 MTB > let c23 = expo(c22)/(1 + expo(c22))
 MTB > print c1 c4 c13 c23
 
  ROW    C1      C4        C13        C23
 
    1     5   0.160   0.162044   0.162253
    2    10   0.255   0.249706   0.250104
    3    15   0.350   0.364181   0.364808
    4    20   0.515   0.496414   0.497237
    5    30   0.740   0.744880   0.745727
===================================================

Worksheet size: 40000000 cells
MTB > help blog
MTB > help blog
MTB > blog c3 c2 = c1;
SUBC> ST.

Binary Logistic Regression


Link Function:  Logit

Response  Information

Variable  Value          Count
C3        Success          404
          Failure          596
C2        Total           1000

Logistic Regression Table
                                                   Odds        95% CI
Predictor       Coef      StDev        Z     P    Ratio    Lower    Upper
Constant     -2.1855     0.1647   -13.27 0.000
C1          0.108719   0.008843    12.29 0.000     1.11     1.10     1.13

Log-Likelihood = -584.382
Test that all slopes are zero: G = 180.437, DF = 1, P-Value = 0.000

Goodness-of-Fit Tests

Method                Chi-Square    DF      P
Pearson                    0.509     3  0.917
Deviance                   0.510     3  0.917
Hosmer-Lemeshow            0.509     3  0.917

Table of Observed and Expected Frequencies:
(See Hosmer-Lemeshow Test for the Pearson Chi-Square Statistic)

                     Group
Value      1     2     3     4     5   Total
Success
  Obs     32    51    70   103   148     404
  Exp     32.4  50.0  73.0  99.4 149.1 
Failure
  Obs    168   149   130    97    52     596
  Exp    167.6 150.0 127.0 100.6  50.9 

  Total  200   200   200   200   200    1000

Measures of Association:
(Between the Response Variable and Predicted Probabilities)

Pairs           Number  Percent     Summary Measures
Concordant      157311    65.3%     Somers' D               0.47
Discordant       43711    18.2%     Goodman-Kruskal Gamma   0.57
Ties             39762    16.5%     Kendall's Tau-a         0.23
Total           240784   100.0%

MTB >  
 
