IBM SPSS Web Report - Output2

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Log
GLM VAR00001 VAR00002 VAR00003 VAR00004 VAR00005 VAR00006 VAR00007 VAR00008 VAR00009 VAR00010 VAR00011 VAR00012 VAR00013 VAR00014 VAR00015 VAR00016 VAR00017 VAR00018 VAR00019 VAR00020 VAR00021 VAR00022 VAR00023 VAR00024 VAR00025 VAR00026 VAR00027 VAR00028 VAR00029 VAR00030 VAR00031 VAR00032 VAR00033
  /WSFACTOR=method 3 Polynomial speaker 11 Polynomial
  /METHOD=SSTYPE(3)
  /PLOT=PROFILE(method speaker speaker*method)
  /EMMEANS=TABLES(OVERALL)
  /EMMEANS=TABLES(method) COMPARE ADJ(BONFERRONI)
  /EMMEANS=TABLES(speaker) COMPARE ADJ(BONFERRONI)
  /EMMEANS=TABLES(method*speaker)
  /PRINT=DESCRIPTIVE ETASQ
  /CRITERIA=ALPHA(.05)
  /WSDESIGN=method speaker method*speaker.
General Linear Model
Within-Subjects FactorsWithin-Subjects Factors, table, Measure, MEASURE_1, 1 layers, 1 levels of column headers and 2 levels of row headers, table with 3 columns and 36 rows
MEASURE_1 MEASURE_1
method speaker Dependent Variable
1 1 VAR00001
2 VAR00002
3 VAR00003
4 VAR00004
5 VAR00005
6 VAR00006
7 VAR00007
8 VAR00008
9 VAR00009
10 VAR00010
11 VAR00011
2 1 VAR00012
2 VAR00013
3 VAR00014
4 VAR00015
5 VAR00016
6 VAR00017
7 VAR00018
8 VAR00019
9 VAR00020
10 VAR00021
11 VAR00022
3 1 VAR00023
2 VAR00024
3 VAR00025
4 VAR00026
5 VAR00027
6 VAR00028
7 VAR00029
8 VAR00030
9 VAR00031
10 VAR00032
11 VAR00033
General Linear Model
Descriptive StatisticsDescriptive Statistics, table, 1 levels of column headers and 1 levels of row headers, table with 4 columns and 35 rows
  Mean Std. Deviation N
VAR00001 71.9533 10.16787 15
VAR00002 63.8600 10.28180 15
VAR00003 65.0200 11.39688 15
VAR00004 74.4000 12.81807 15
VAR00005 84.8133 6.49878 15
VAR00006 75.5600 8.52164 15
VAR00007 77.8133 7.07217 15
VAR00008 69.3733 8.49954 15
VAR00009 77.2867 12.74592 15
VAR00010 79.8000 6.26738 15
VAR00011 69.3067 12.48682 15
VAR00012 81.6000 12.20345 15
VAR00013 76.3400 12.93107 15
VAR00014 71.8133 13.77798 15
VAR00015 67.2200 12.87990 15
VAR00016 84.1267 8.67916 15
VAR00017 74.1667 10.70552 15
VAR00018 76.8133 12.00386 15
VAR00019 64.2467 12.28081 15
VAR00020 80.8467 14.25762 15
VAR00021 78.6667 12.05545 15
VAR00022 72.9400 15.33976 15
VAR00023 7.0533 5.86623 15
VAR00024 6.6267 5.75009 15
VAR00025 8.7533 7.72620 15
VAR00026 5.9200 5.98858 15
VAR00027 7.8000 6.66065 15
VAR00028 5.3867 5.77258 15
VAR00029 5.8200 6.55038 15
VAR00030 6.2933 5.47742 15
VAR00031 5.5067 5.07901 15
VAR00032 6.6933 7.20847 15
VAR00033 6.2000 6.45855 15
General Linear Model
Multivariate TestsaMultivariate Tests, table, 1 levels of column headers and 2 levels of row headers, table with 8 columns and 17 rows
Effect Value F Hypothesis df Error df Sig. Partial Eta Squared
method Pillai's Trace .985 421.872b 2.000 13.000 .000 .985
Wilks' Lambda .015 421.872b 2.000 13.000 .000 .985
Hotelling's Trace 64.903 421.872b 2.000 13.000 .000 .985
Roy's Largest Root 64.903 421.872b 2.000 13.000 .000 .985
speaker Pillai's Trace .995 92.580b 10.000 5.000 .000 .995
Wilks' Lambda .005 92.580b 10.000 5.000 .000 .995
Hotelling's Trace 185.160 92.580b 10.000 5.000 .000 .995
Roy's Largest Root 185.160 92.580b 10.000 5.000 .000 .995
method * speaker Pillai's Trace .c . . . . .
Wilks' Lambda .c . . . . .
Hotelling's Trace .c . . . . .
Roy's Largest Root .c . . . . .
a. Design: Intercept
Within Subjects Design: method + speaker + method * speaker
b. Exact statistic
c. Cannot produce multivariate test statistics because of insufficient residual degrees of freedom.
General Linear Model
Mauchly's Test of SphericityaMauchly's Test of Sphericity, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 1 levels of row headers, table with 8 columns and 10 rows
MEASURE_1 MEASURE_1
Within Subjects Effect Mauchly's W Approx. Chi-Square df Sig. Epsilonb
Greenhouse-Geisser Huynh-Feldt Lower-bound
method .582 7.033 2 .030 .705 .761 .500
speaker .000 84.031 54 .012 .526 .881 .100
method * speaker .000 . 209 . .341 .698 .050
Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix.
a. Design: Intercept
Within Subjects Design: method + speaker + method * speaker
b. May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in the Tests of Within-Subjects Effects table.
General Linear Model
Tests of Within-Subjects EffectsTests of Within-Subjects Effects, table, Measure, MEASURE_1, 1 layers, 1 levels of column headers and 2 levels of row headers, table with 8 columns and 27 rows
MEASURE_1 MEASURE_1
Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared
method Sphericity Assumed 507447.590 2 253723.795 539.191 .000 .975
Greenhouse-Geisser 507447.590 1.411 359740.974 539.191 .000 .975
Huynh-Feldt 507447.590 1.522 333446.790 539.191 .000 .975
Lower-bound 507447.590 1.000 507447.590 539.191 .000 .975
Error(method) Sphericity Assumed 13175.776 28 470.563      
Greenhouse-Geisser 13175.776 19.748 667.186      
Huynh-Feldt 13175.776 21.306 618.420      
Lower-bound 13175.776 14.000 941.127      
speaker Sphericity Assumed 5954.725 10 595.473 29.316 .000 .677
Greenhouse-Geisser 5954.725 5.263 1131.340 29.316 .000 .677
Huynh-Feldt 5954.725 8.808 676.061 29.316 .000 .677
Lower-bound 5954.725 1.000 5954.725 29.316 .000 .677
Error(speaker) Sphericity Assumed 2843.662 140 20.312      
Greenhouse-Geisser 2843.662 73.688 38.591      
Huynh-Feldt 2843.662 123.312 23.061      
Lower-bound 2843.662 14.000 203.119      
method * speaker Sphericity Assumed 5854.217 20 292.711 20.513 .000 .594
Greenhouse-Geisser 5854.217 6.817 858.769 20.513 .000 .594
Huynh-Feldt 5854.217 13.957 419.440 20.513 .000 .594
Lower-bound 5854.217 1.000 5854.217 20.513 .000 .594
Error(method*speaker) Sphericity Assumed 3995.557 280 14.270      
Greenhouse-Geisser 3995.557 95.438 41.866      
Huynh-Feldt 3995.557 195.401 20.448      
Lower-bound 3995.557 14.000 285.397      
General Linear Model
Tests of Within-Subjects ContrastsTests of Within-Subjects Contrasts, table, Measure, MEASURE_1, 1 layers, 1 levels of column headers and 3 levels of row headers, table with 9 columns and 67 rows
MEASURE_1 MEASURE_1
Source method speaker Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared
method Linear   370476.512 1 370476.512 893.427 .000 .985
Quadratic   136971.078 1 136971.078 260.175 .000 .949
Error(method) Linear   5805.364 14 414.669      
Quadratic   7370.412 14 526.458      
speaker   Linear 56.149 1 56.149 6.236 .026 .308
Quadratic 73.152 1 73.152 3.182 .096 .185
Cubic 255.768 1 255.768 6.864 .020 .329
Order 4 247.625 1 247.625 18.528 .001 .570
Order 5 2170.224 1 2170.224 113.729 .000 .890
Order 6 723.796 1 723.796 27.899 .000 .666
Order 7 351.650 1 351.650 18.010 .001 .563
Order 8 198.171 1 198.171 12.201 .004 .466
Order 9 .055 1 .055 .002 .966 .000
Order 10 1878.135 1 1878.135 182.558 .000 .929
Error(speaker)   Linear 126.051 14 9.004      
Quadratic 321.893 14 22.992      
Cubic 521.678 14 37.263      
Order 4 187.112 14 13.365      
Order 5 267.155 14 19.082      
Order 6 363.202 14 25.943      
Order 7 273.357 14 19.525      
Order 8 227.397 14 16.243      
Order 9 411.788 14 29.413      
Order 10 144.030 14 10.288      
method * speaker Linear Linear 495.477 1 495.477 39.575 .000 .739
Quadratic 582.124 1 582.124 44.032 .000 .759
Cubic 153.023 1 153.023 15.569 .001 .527
Order 4 279.434 1 279.434 38.142 .000 .732
Order 5 1197.358 1 1197.358 143.981 .000 .911
Order 6 155.116 1 155.116 8.109 .013 .367
Order 7 129.057 1 129.057 10.630 .006 .432
Order 8 8.275 1 8.275 .599 .452 .041
Order 9 88.345 1 88.345 3.626 .078 .206
Order 10 235.232 1 235.232 28.467 .000 .670
Quadratic Linear 207.742 1 207.742 14.337 .002 .506
Quadratic 621.116 1 621.116 32.497 .000 .699
Cubic 111.138 1 111.138 11.833 .004 .458
Order 4 .102 1 .102 .008 .930 .001
Order 5 1.650 1 1.650 .090 .768 .006
Order 6 380.183 1 380.183 10.031 .007 .417
Order 7 218.089 1 218.089 19.516 .001 .582
Order 8 484.053 1 484.053 27.900 .000 .666
Order 9 5.494 1 5.494 .463 .508 .032
Order 10 501.209 1 501.209 114.499 .000 .891
Error(method*speaker) Linear Linear 175.277 14 12.520      
Quadratic 185.088 14 13.221      
Cubic 137.601 14 9.829      
Order 4 102.567 14 7.326      
Order 5 116.425 14 8.316      
Order 6 267.809 14 19.129      
Order 7 169.965 14 12.140      
Order 8 193.441 14 13.817      
Order 9 341.081 14 24.363      
Order 10 115.688 14 8.263      
Quadratic Linear 202.859 14 14.490      
Quadratic 267.584 14 19.113      
Cubic 131.486 14 9.392      
Order 4 175.774 14 12.555      
Order 5 255.344 14 18.239      
Order 6 530.632 14 37.902      
Order 7 156.445 14 11.175      
Order 8 242.896 14 17.350      
Order 9 166.310 14 11.879      
Order 10 61.284 14 4.377      
General Linear Model
Tests of Between-Subjects EffectsTests of Between-Subjects Effects, table, Measure, MEASURE_1, Transformed Variable, Average, 1 layers, 1 levels of column headers and 1 levels of row headers, table with 7 columns and 6 rows
MEASURE_1 MEASURE_1
Average Average
Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared
Intercept 1329167.455 1 1329167.455 721.530 .000 .981
Error 25790.107 14 1842.151      
Estimated Marginal Means
1. Grand Mean1. Grand Mean, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 0 levels of row headers, table with 4 columns and 5 rows
MEASURE_1 MEASURE_1
Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
51.819 1.929 47.681 55.956
2. method
EstimatesEstimates, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 1 levels of row headers, table with 5 columns and 7 rows
MEASURE_1 MEASURE_1
method Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 73.562 2.291 68.648 78.477
2 75.344 3.036 68.833 81.855
3 6.550 1.550 3.226 9.875
2. method
Pairwise ComparisonsPairwise Comparisons, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 2 levels of row headers, table with 7 columns and 13 rows
MEASURE_1 MEASURE_1
(I) method (J) method Mean Difference (I-J) Std. Error Sig.b 95% Confidence Interval for Differenceb
Lower Bound Upper Bound
1 2 -1.781 1.704 .941 -6.412 2.850
3 67.012* 2.242 .000 60.919 73.105
2 1 1.781 1.704 .941 -2.850 6.412
3 68.793* 3.030 .000 60.558 77.028
3 1 -67.012* 2.242 .000 -73.105 -60.919
2 -68.793* 3.030 .000 -77.028 -60.558
Based on estimated marginal means
*. The mean difference is significant at the
b. Adjustment for multiple comparisons: Bonferroni.
2. method
Multivariate TestsMultivariate Tests, table, 1 levels of column headers and 1 levels of row headers, table with 7 columns and 8 rows
  Value F Hypothesis df Error df Sig. Partial Eta Squared
Pillai's trace .985 421.872a 2.000 13.000 .000 .985
Wilks' lambda .015 421.872a 2.000 13.000 .000 .985
Hotelling's trace 64.903 421.872a 2.000 13.000 .000 .985
Roy's largest root 64.903 421.872a 2.000 13.000 .000 .985
Each F tests the multivariate effect of method. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.
a. Exact statistic
3. speaker
EstimatesEstimates, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 1 levels of row headers, table with 5 columns and 15 rows
MEASURE_1 MEASURE_1
speaker Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 53.536 1.995 49.257 57.814
2 48.942 2.095 44.448 53.436
3 48.529 2.354 43.480 53.578
4 49.180 2.228 44.401 53.959
5 58.913 1.625 55.428 62.399
6 51.704 1.775 47.897 55.512
7 53.482 1.704 49.829 57.136
8 46.638 1.861 42.646 50.629
9 54.547 2.364 49.477 59.616
10 55.053 1.674 51.463 58.643
11 49.482 2.455 44.217 54.747
3. speaker
Pairwise ComparisonsPairwise Comparisons, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 2 levels of row headers, table with 7 columns and 117 rows
MEASURE_1 MEASURE_1
(I) speaker (J) speaker Mean Difference (I-J) Std. Error Sig.b 95% Confidence Interval for Differenceb
Lower Bound Upper Bound
1 2 4.593* .991 .021 .440 8.747
3 5.007* 1.128 .031 .280 9.734
4 4.356* .862 .010 .743 7.968
5 -5.378* .872 .001 -9.030 -1.726
6 1.831 1.094 1.000 -2.752 6.415
7 .053 .780 1.000 -3.215 3.321
8 6.898* 1.044 .001 2.522 11.273
9 -1.011 .798 1.000 -4.355 2.333
10 -1.518 .865 1.000 -5.140 2.105
11 4.053 1.080 .118 -.471 8.578
2 1 -4.593* .991 .021 -8.747 -.440
3 .413 1.042 1.000 -3.954 4.781
4 -.238 .870 1.000 -3.881 3.405
5 -9.971* .836 .000 -13.475 -6.467
6 -2.762 .774 .170 -6.006 .482
7 -4.540* .754 .002 -7.699 -1.381
8 2.304 .907 1.000 -1.495 6.104
9 -5.604* .730 .000 -8.663 -2.546
10 -6.111* .885 .000 -9.820 -2.403
11 -.540 1.093 1.000 -5.117 4.037
3 1 -5.007* 1.128 .031 -9.734 -.280
2 -.413 1.042 1.000 -4.781 3.954
4 -.651 .859 1.000 -4.251 2.949
5 -10.384* .913 .000 -14.207 -6.562
6 -3.176 .874 .150 -6.838 .487
7 -4.953* .990 .011 -9.102 -.805
8 1.891 1.032 1.000 -2.433 6.216
9 -6.018* 1.119 .005 -10.706 -1.329
10 -6.524* 1.002 .001 -10.722 -2.327
11 -.953 .829 1.000 -4.425 2.519
4 1 -4.356* .862 .010 -7.968 -.743
2 .238 .870 1.000 -3.405 3.881
3 .651 .859 1.000 -2.949 4.251
5 -9.733* .921 .000 -13.593 -5.874
6 -2.524 .911 .826 -6.341 1.293
7 -4.302* .911 .018 -8.118 -.486
8 2.542 1.172 1.000 -2.367 7.452
9 -5.367* .873 .001 -9.026 -1.708
10 -5.873* 1.057 .004 -10.300 -1.447
11 -.302 .892 1.000 -4.039 3.434
5 1 5.378* .872 .001 1.726 9.030
2 9.971* .836 .000 6.467 13.475
3 10.384* .913 .000 6.562 14.207
4 9.733* .921 .000 5.874 13.593
6 7.209* .615 .000 4.631 9.786
7 5.431* .710 .000 2.458 8.405
8 12.276* .842 .000 8.749 15.802
9 4.367 1.151 .109 -.457 9.190
10 3.860* .554 .000 1.537 6.183
11 9.431* 1.157 .000 4.585 14.277
6 1 -1.831 1.094 1.000 -6.415 2.752
2 2.762 .774 .170 -.482 6.006
3 3.176 .874 .150 -.487 6.838
4 2.524 .911 .826 -1.293 6.341
5 -7.209* .615 .000 -9.786 -4.631
7 -1.778 .809 1.000 -5.167 1.612
8 5.067* .841 .002 1.543 8.591
9 -2.842 1.153 1.000 -7.672 1.988
10 -3.349* .775 .039 -6.597 -.101
11 2.222 .884 1.000 -1.482 5.926
7 1 -.053 .780 1.000 -3.321 3.215
2 4.540* .754 .002 1.381 7.699
3 4.953* .990 .011 .805 9.102
4 4.302* .911 .018 .486 8.118
5 -5.431* .710 .000 -8.405 -2.458
6 1.778 .809 1.000 -1.612 5.167
8 6.844* .660 .000 4.081 9.607
9 -1.064 .931 1.000 -4.966 2.837
10 -1.571 .734 1.000 -4.644 1.502
11 4.000 1.224 .308 -1.126 9.126
8 1 -6.898* 1.044 .001 -11.273 -2.522
2 -2.304 .907 1.000 -6.104 1.495
3 -1.891 1.032 1.000 -6.216 2.433
4 -2.542 1.172 1.000 -7.452 2.367
5 -12.276* .842 .000 -15.802 -8.749
6 -5.067* .841 .002 -8.591 -1.543
7 -6.844* .660 .000 -9.607 -4.081
9 -7.909* 1.267 .001 -13.215 -2.602
10 -8.416* .819 .000 -11.849 -4.983
11 -2.844 1.159 1.000 -7.702 2.013
9 1 1.011 .798 1.000 -2.333 4.355
2 5.604* .730 .000 2.546 8.663
3 6.018* 1.119 .005 1.329 10.706
4 5.367* .873 .001 1.708 9.026
5 -4.367 1.151 .109 -9.190 .457
6 2.842 1.153 1.000 -1.988 7.672
7 1.064 .931 1.000 -2.837 4.966
8 7.909* 1.267 .001 2.602 13.215
10 -.507 1.200 1.000 -5.535 4.521
11 5.064* 1.131 .029 .325 9.804
10 1 1.518 .865 1.000 -2.105 5.140
2 6.111* .885 .000 2.403 9.820
3 6.524* 1.002 .001 2.327 10.722
4 5.873* 1.057 .004 1.447 10.300
5 -3.860* .554 .000 -6.183 -1.537
6 3.349* .775 .039 .101 6.597
7 1.571 .734 1.000 -1.502 4.644
8 8.416* .819 .000 4.983 11.849
9 .507 1.200 1.000 -4.521 5.535
11 5.571* 1.098 .009 .971 10.172
11 1 -4.053 1.080 .118 -8.578 .471
2 .540 1.093 1.000 -4.037 5.117
3 .953 .829 1.000 -2.519 4.425
4 .302 .892 1.000 -3.434 4.039
5 -9.431* 1.157 .000 -14.277 -4.585
6 -2.222 .884 1.000 -5.926 1.482
7 -4.000 1.224 .308 -9.126 1.126
8 2.844 1.159 1.000 -2.013 7.702
9 -5.064* 1.131 .029 -9.804 -.325
10 -5.571* 1.098 .009 -10.172 -.971
Based on estimated marginal means
*. The mean difference is significant at the
b. Adjustment for multiple comparisons: Bonferroni.
3. speaker
Multivariate TestsMultivariate Tests, table, 1 levels of column headers and 1 levels of row headers, table with 7 columns and 8 rows
  Value F Hypothesis df Error df Sig. Partial Eta Squared
Pillai's trace .995 92.580a 10.000 5.000 .000 .995
Wilks' lambda .005 92.580a 10.000 5.000 .000 .995
Hotelling's trace 185.160 92.580a 10.000 5.000 .000 .995
Roy's largest root 185.160 92.580a 10.000 5.000 .000 .995
Each F tests the multivariate effect of speaker. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.
a. Exact statistic
Estimated Marginal Means
4. method * speaker4. method * speaker, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 2 levels of row headers, table with 6 columns and 37 rows
MEASURE_1 MEASURE_1
method speaker Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 1 71.953 2.625 66.323 77.584
2 63.860 2.655 58.166 69.554
3 65.020 2.943 58.709 71.331
4 74.400 3.310 67.302 81.498
5 84.813 1.678 81.214 88.412
6 75.560 2.200 70.841 80.279
7 77.813 1.826 73.897 81.730
8 69.373 2.195 64.666 74.080
9 77.287 3.291 70.228 84.345
10 79.800 1.618 76.329 83.271
11 69.307 3.224 62.392 76.222
2 1 81.600 3.151 74.842 88.358
2 76.340 3.339 69.179 83.501
3 71.813 3.557 64.183 79.443
4 67.220 3.326 60.087 74.353
5 84.127 2.241 79.320 88.933
6 74.167 2.764 68.238 80.095
7 76.813 3.099 70.166 83.461
8 64.247 3.171 57.446 71.048
9 80.847 3.681 72.951 88.742
10 78.667 3.113 71.991 85.343
11 72.940 3.961 64.445 81.435
3 1 7.053 1.515 3.805 10.302
2 6.627 1.485 3.442 9.811
3 8.753 1.995 4.475 13.032
4 5.920 1.546 2.604 9.236
5 7.800 1.720 4.111 11.489
6 5.387 1.490 2.190 8.583
7 5.820 1.691 2.193 9.447
8 6.293 1.414 3.260 9.327
9 5.507 1.311 2.694 8.319
10 6.693 1.861 2.701 10.685
11 6.200 1.668 2.623 9.777
Profile Plots
method: 3 Estimated Marginal Means: 6.5503 method: 2 Estimated Marginal Means: 75.344 method: 1 Estimated Marginal Means: 73.562 method: 2 Estimated Marginal Means: 75.344 method: 1 Estimated Marginal Means: 73.562 .00 20.00 40.00 60.00 80.00 80.00 60.00 40.00 20.00 .00 1 2 3 3 2 1
Profile Plots
speaker: 11 Estimated Marginal Means: 49.482 speaker: 10 Estimated Marginal Means: 55.053 speaker: 9 Estimated Marginal Means: 54.547 speaker: 8 Estimated Marginal Means: 46.638 speaker: 7 Estimated Marginal Means: 53.482 speaker: 6 Estimated Marginal Means: 51.704 speaker: 5 Estimated Marginal Means: 58.913 speaker: 4 Estimated Marginal Means: 49.18 speaker: 3 Estimated Marginal Means: 48.529 speaker: 2 Estimated Marginal Means: 48.942 speaker: 1 Estimated Marginal Means: 53.536 speaker: 10 Estimated Marginal Means: 55.053 speaker: 9 Estimated Marginal Means: 54.547 speaker: 8 Estimated Marginal Means: 46.638 speaker: 7 Estimated Marginal Means: 53.482 speaker: 6 Estimated Marginal Means: 51.704 speaker: 5 Estimated Marginal Means: 58.913 speaker: 4 Estimated Marginal Means: 49.18 speaker: 3 Estimated Marginal Means: 48.529 speaker: 2 Estimated Marginal Means: 48.942 speaker: 1 Estimated Marginal Means: 53.536 47.50 50.00 52.50 55.00 57.50 60.00 60.00 57.50 55.00 52.50 50.00 47.50 1 2 3 4 5 6 7 8 9 10 11 11 10 9 8 7 6 5 4 3 2 1
Profile Plots
speaker: 11 Estimated Marginal Means: 6.20 method: 3 speaker: 10 Estimated Marginal Means: 6.6933 method: 3 speaker: 9 Estimated Marginal Means: 5.5067 method: 3 speaker: 8 Estimated Marginal Means: 6.2933 method: 3 speaker: 7 Estimated Marginal Means: 5.82 method: 3 speaker: 6 Estimated Marginal Means: 5.3867 method: 3 speaker: 5 Estimated Marginal Means: 7.80 method: 3 speaker: 4 Estimated Marginal Means: 5.92 method: 3 speaker: 3 Estimated Marginal Means: 8.7533 method: 3 speaker: 2 Estimated Marginal Means: 6.6267 method: 3 speaker: 1 Estimated Marginal Means: 7.0533 method: 3 speaker: 11 Estimated Marginal Means: 72.94 method: 2 speaker: 10 Estimated Marginal Means: 78.667 method: 2 speaker: 9 Estimated Marginal Means: 80.847 method: 2 speaker: 8 Estimated Marginal Means: 64.247 method: 2 speaker: 7 Estimated Marginal Means: 76.813 method: 2 speaker: 6 Estimated Marginal Means: 74.167 method: 2 speaker: 5 Estimated Marginal Means: 84.127 method: 2 speaker: 4 Estimated Marginal Means: 67.22 method: 2 speaker: 3 Estimated Marginal Means: 71.813 method: 2 speaker: 2 Estimated Marginal Means: 76.34 method: 2 speaker: 1 Estimated Marginal Means: 81.60 method: 2 speaker: 11 Estimated Marginal Means: 69.307 method: 1 speaker: 10 Estimated Marginal Means: 79.80 method: 1 speaker: 9 Estimated Marginal Means: 77.287 method: 1 speaker: 8 Estimated Marginal Means: 69.373 method: 1 speaker: 7 Estimated Marginal Means: 77.813 method: 1 speaker: 6 Estimated Marginal Means: 75.56 method: 1 speaker: 5 Estimated Marginal Means: 84.813 method: 1 speaker: 4 Estimated Marginal Means: 74.40 method: 1 speaker: 3 Estimated Marginal Means: 65.02 method: 1 speaker: 2 Estimated Marginal Means: 63.86 method: 1 speaker: 1 Estimated Marginal Means: 71.953 method: 1 speaker: 10 Estimated Marginal Means: 6.6933 method: 3 speaker: 9 Estimated Marginal Means: 5.5067 method: 3 speaker: 8 Estimated Marginal Means: 6.2933 method: 3 speaker: 7 Estimated Marginal Means: 5.82 method: 3 speaker: 6 Estimated Marginal Means: 5.3867 method: 3 speaker: 5 Estimated Marginal Means: 7.80 method: 3 speaker: 4 Estimated Marginal Means: 5.92 method: 3 speaker: 3 Estimated Marginal Means: 8.7533 method: 3 speaker: 2 Estimated Marginal Means: 6.6267 method: 3 speaker: 1 Estimated Marginal Means: 7.0533 method: 3 speaker: 10 Estimated Marginal Means: 78.667 method: 2 speaker: 9 Estimated Marginal Means: 80.847 method: 2 speaker: 8 Estimated Marginal Means: 64.247 method: 2 speaker: 7 Estimated Marginal Means: 76.813 method: 2 speaker: 6 Estimated Marginal Means: 74.167 method: 2 speaker: 5 Estimated Marginal Means: 84.127 method: 2 speaker: 4 Estimated Marginal Means: 67.22 method: 2 speaker: 3 Estimated Marginal Means: 71.813 method: 2 speaker: 2 Estimated Marginal Means: 76.34 method: 2 speaker: 1 Estimated Marginal Means: 81.60 method: 2 speaker: 10 Estimated Marginal Means: 79.80 method: 1 speaker: 9 Estimated Marginal Means: 77.287 method: 1 speaker: 8 Estimated Marginal Means: 69.373 method: 1 speaker: 7 Estimated Marginal Means: 77.813 method: 1 speaker: 6 Estimated Marginal Means: 75.56 method: 1 speaker: 5 Estimated Marginal Means: 84.813 method: 1 speaker: 4 Estimated Marginal Means: 74.40 method: 1 speaker: 3 Estimated Marginal Means: 65.02 method: 1 speaker: 2 Estimated Marginal Means: 63.86 method: 1 speaker: 1 Estimated Marginal Means: 71.953 method: 1 .00 20.00 40.00 60.00 80.00 100.00 100.00 80.00 60.00 40.00 20.00 .00 1 2 3 4 5 6 7 8 9 10 11 11 10 9 8 7 6 5 4 3 2 1
IBM SPSS Web Report
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