|
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method | speaker | style | Dependent Variable | ||
1 | 1 | 1 | VAR00001 | ||
2 | VAR00002 | ||||
3 | VAR00003 | ||||
2 | 1 | VAR00004 | |||
2 | VAR00005 | ||||
3 | VAR00006 | ||||
3 | 1 | VAR00007 | |||
2 | VAR00008 | ||||
3 | VAR00009 | ||||
4 | 1 | VAR00010 | |||
2 | VAR00011 | ||||
3 | VAR00012 | ||||
2 | 1 | 1 | VAR00013 | ||
2 | VAR00014 | ||||
3 | VAR00015 | ||||
2 | 1 | VAR00016 | |||
2 | VAR00017 | ||||
3 | VAR00018 | ||||
3 | 1 | VAR00019 | |||
2 | VAR00020 | ||||
3 | VAR00021 | ||||
4 | 1 | VAR00022 | |||
2 | VAR00023 | ||||
3 | VAR00024 | ||||
3 | 1 | 1 | VAR00025 | ||
2 | VAR00026 | ||||
3 | VAR00027 | ||||
2 | 1 | VAR00028 | |||
2 | VAR00029 | ||||
3 | VAR00030 | ||||
3 | 1 | VAR00031 | |||
2 | VAR00032 | ||||
3 | VAR00033 | ||||
4 | 1 | VAR00034 | |||
2 | VAR00035 | ||||
3 | VAR00036 | ||||
Effect | Value | F | Hypothesis df | Error df | Sig. | |
method | Pillai's Trace | .683 | 14.005b | 2.000 | 13.000 | .001 |
Wilks' Lambda | .317 | 14.005b | 2.000 | 13.000 | .001 | |
Hotelling's Trace | 2.155 | 14.005b | 2.000 | 13.000 | .001 | |
Roy's Largest Root | 2.155 | 14.005b | 2.000 | 13.000 | .001 | |
speaker | Pillai's Trace | .620 | 6.533b | 3.000 | 12.000 | .007 |
Wilks' Lambda | .380 | 6.533b | 3.000 | 12.000 | .007 | |
Hotelling's Trace | 1.633 | 6.533b | 3.000 | 12.000 | .007 | |
Roy's Largest Root | 1.633 | 6.533b | 3.000 | 12.000 | .007 | |
style | Pillai's Trace | .742 | 18.734b | 2.000 | 13.000 | .000 |
Wilks' Lambda | .258 | 18.734b | 2.000 | 13.000 | .000 | |
Hotelling's Trace | 2.882 | 18.734b | 2.000 | 13.000 | .000 | |
Roy's Largest Root | 2.882 | 18.734b | 2.000 | 13.000 | .000 | |
method * speaker | Pillai's Trace | .842 | 7.965b | 6.000 | 9.000 | .003 |
Wilks' Lambda | .158 | 7.965b | 6.000 | 9.000 | .003 | |
Hotelling's Trace | 5.310 | 7.965b | 6.000 | 9.000 | .003 | |
Roy's Largest Root | 5.310 | 7.965b | 6.000 | 9.000 | .003 | |
method * style | Pillai's Trace | .313 | 1.254b | 4.000 | 11.000 | .345 |
Wilks' Lambda | .687 | 1.254b | 4.000 | 11.000 | .345 | |
Hotelling's Trace | .456 | 1.254b | 4.000 | 11.000 | .345 | |
Roy's Largest Root | .456 | 1.254b | 4.000 | 11.000 | .345 | |
speaker * style | Pillai's Trace | .742 | 4.316b | 6.000 | 9.000 | .025 |
Wilks' Lambda | .258 | 4.316b | 6.000 | 9.000 | .025 | |
Hotelling's Trace | 2.878 | 4.316b | 6.000 | 9.000 | .025 | |
Roy's Largest Root | 2.878 | 4.316b | 6.000 | 9.000 | .025 | |
method * speaker * style | Pillai's Trace | .796 | .975b | 12.000 | 3.000 | .584 |
Wilks' Lambda | .204 | .975b | 12.000 | 3.000 | .584 | |
Hotelling's Trace | 3.900 | .975b | 12.000 | 3.000 | .584 | |
Roy's Largest Root | 3.900 | .975b | 12.000 | 3.000 | .584 | |
a. Design: Intercept Within Subjects Design: method + speaker + style + method * speaker + method * style + speaker * style + method * speaker * style |
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b. Exact statistic | ||||||
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Within Subjects Effect | Mauchly's W | Approx. Chi-Square | df | Sig. | Epsilonb | ||||
Greenhouse-Geisser | Huynh-Feldt | Lower-bound | |||||||
method | .600 | 6.631 | 2 | .036 | .715 | .773 | .500 | ||
speaker | .691 | 4.708 | 5 | .454 | .793 | .967 | .333 | ||
style | .536 | 8.098 | 2 | .017 | .683 | .732 | .500 | ||
method * speaker | .023 | 44.493 | 20 | .002 | .395 | .481 | .167 | ||
method * style | .131 | 25.247 | 9 | .003 | .531 | .628 | .250 | ||
speaker * style | .225 | 17.593 | 20 | .630 | .673 | .980 | .167 | ||
method * speaker * style | .000 | 142.944 | 77 | .000 | .369 | .561 | .083 | ||
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 + style + method * speaker + method * style + speaker * style + method * speaker * style |
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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. | |||||||||
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Source | Type III Sum of Squares | df | Mean Square | F | Sig. | |||
method | Sphericity Assumed | 3211.065 | 2 | 1605.533 | 7.199 | .003 | ||
Greenhouse-Geisser | 3211.065 | 1.429 | 2247.057 | 7.199 | .008 | |||
Huynh-Feldt | 3211.065 | 1.546 | 2076.974 | 7.199 | .007 | |||
Lower-bound | 3211.065 | 1.000 | 3211.065 | 7.199 | .018 | |||
Error(method) | Sphericity Assumed | 6244.801 | 28 | 223.029 | ||||
Greenhouse-Geisser | 6244.801 | 20.006 | 312.144 | |||||
Huynh-Feldt | 6244.801 | 21.644 | 288.518 | |||||
Lower-bound | 6244.801 | 14.000 | 446.057 | |||||
speaker | Sphericity Assumed | 7847.006 | 3 | 2615.669 | 12.168 | .000 | ||
Greenhouse-Geisser | 7847.006 | 2.380 | 3296.534 | 12.168 | .000 | |||
Huynh-Feldt | 7847.006 | 2.901 | 2705.156 | 12.168 | .000 | |||
Lower-bound | 7847.006 | 1.000 | 7847.006 | 12.168 | .004 | |||
Error(speaker) | Sphericity Assumed | 9028.299 | 42 | 214.960 | ||||
Greenhouse-Geisser | 9028.299 | 33.325 | 270.914 | |||||
Huynh-Feldt | 9028.299 | 40.611 | 222.314 | |||||
Lower-bound | 9028.299 | 14.000 | 644.879 | |||||
style | Sphericity Assumed | 24383.752 | 2 | 12191.876 | 30.991 | .000 | ||
Greenhouse-Geisser | 24383.752 | 1.366 | 17844.459 | 30.991 | .000 | |||
Huynh-Feldt | 24383.752 | 1.464 | 16654.300 | 30.991 | .000 | |||
Lower-bound | 24383.752 | 1.000 | 24383.752 | 30.991 | .000 | |||
Error(style) | Sphericity Assumed | 11015.044 | 28 | 393.394 | ||||
Greenhouse-Geisser | 11015.044 | 19.130 | 575.786 | |||||
Huynh-Feldt | 11015.044 | 20.498 | 537.383 | |||||
Lower-bound | 11015.044 | 14.000 | 786.789 | |||||
method * speaker | Sphericity Assumed | 3745.441 | 6 | 624.240 | 27.181 | .000 | ||
Greenhouse-Geisser | 3745.441 | 2.370 | 1580.471 | 27.181 | .000 | |||
Huynh-Feldt | 3745.441 | 2.885 | 1298.466 | 27.181 | .000 | |||
Lower-bound | 3745.441 | 1.000 | 3745.441 | 27.181 | .000 | |||
Error(method*speaker) | Sphericity Assumed | 1929.132 | 84 | 22.966 | ||||
Greenhouse-Geisser | 1929.132 | 33.178 | 58.146 | |||||
Huynh-Feldt | 1929.132 | 40.383 | 47.771 | |||||
Lower-bound | 1929.132 | 14.000 | 137.795 | |||||
method * style | Sphericity Assumed | 449.011 | 4 | 112.253 | 2.450 | .057 | ||
Greenhouse-Geisser | 449.011 | 2.122 | 211.560 | 2.450 | .101 | |||
Huynh-Feldt | 449.011 | 2.512 | 178.752 | 2.450 | .089 | |||
Lower-bound | 449.011 | 1.000 | 449.011 | 2.450 | .140 | |||
Error(method*style) | Sphericity Assumed | 2566.086 | 56 | 45.823 | ||||
Greenhouse-Geisser | 2566.086 | 29.713 | 86.361 | |||||
Huynh-Feldt | 2566.086 | 35.167 | 72.969 | |||||
Lower-bound | 2566.086 | 14.000 | 183.292 | |||||
speaker * style | Sphericity Assumed | 2399.724 | 6 | 399.954 | 5.244 | .000 | ||
Greenhouse-Geisser | 2399.724 | 4.039 | 594.157 | 5.244 | .001 | |||
Huynh-Feldt | 2399.724 | 5.881 | 408.036 | 5.244 | .000 | |||
Lower-bound | 2399.724 | 1.000 | 2399.724 | 5.244 | .038 | |||
Error(speaker*style) | Sphericity Assumed | 6406.066 | 84 | 76.263 | ||||
Greenhouse-Geisser | 6406.066 | 56.544 | 113.293 | |||||
Huynh-Feldt | 6406.066 | 82.336 | 77.804 | |||||
Lower-bound | 6406.066 | 14.000 | 457.576 | |||||
method * speaker * style | Sphericity Assumed | 630.632 | 12 | 52.553 | 2.879 | .001 | ||
Greenhouse-Geisser | 630.632 | 4.430 | 142.357 | 2.879 | .026 | |||
Huynh-Feldt | 630.632 | 6.734 | 93.643 | 2.879 | .010 | |||
Lower-bound | 630.632 | 1.000 | 630.632 | 2.879 | .112 | |||
Error(method*speaker*style) | Sphericity Assumed | 3066.388 | 168 | 18.252 | ||||
Greenhouse-Geisser | 3066.388 | 62.019 | 49.443 | |||||
Huynh-Feldt | 3066.388 | 94.282 | 32.524 | |||||
Lower-bound | 3066.388 | 14.000 | 219.028 | |||||
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Source | method | speaker | style | Type III Sum of Squares | df | Mean Square | F | Sig. | ||
method | Linear | 3113.264 | 1 | 3113.264 | 14.600 | .002 | ||||
Quadratic | 97.801 | 1 | 97.801 | .420 | .527 | |||||
Error(method) | Linear | 2985.352 | 14 | 213.239 | ||||||
Quadratic | 3259.449 | 14 | 232.818 | |||||||
speaker | Linear | 2417.472 | 1 | 2417.472 | 9.075 | .009 | ||||
Quadratic | 5401.286 | 1 | 5401.286 | 21.013 | .000 | |||||
Cubic | 28.247 | 1 | 28.247 | .233 | .637 | |||||
Error(speaker) | Linear | 3729.382 | 14 | 266.384 | ||||||
Quadratic | 3598.582 | 14 | 257.042 | |||||||
Cubic | 1700.335 | 14 | 121.453 | |||||||
style | Linear | 15199.169 | 1 | 15199.169 | 28.524 | .000 | ||||
Quadratic | 9184.584 | 1 | 9184.584 | 36.169 | .000 | |||||
Error(style) | Linear | 7459.941 | 14 | 532.853 | ||||||
Quadratic | 3555.103 | 14 | 253.936 | |||||||
method * speaker | Linear | Linear | 2272.129 | 1 | 2272.129 | 35.654 | .000 | |||
Quadratic | 671.489 | 1 | 671.489 | 36.826 | .000 | |||||
Cubic | 64.727 | 1 | 64.727 | 8.726 | .010 | |||||
Quadratic | Linear | 384.356 | 1 | 384.356 | 19.492 | .001 | ||||
Quadratic | 327.434 | 1 | 327.434 | 20.125 | .001 | |||||
Cubic | 25.306 | 1 | 25.306 | 2.036 | .175 | |||||
Error(method*speaker) | Linear | Linear | 892.178 | 14 | 63.727 | |||||
Quadratic | 255.279 | 14 | 18.234 | |||||||
Cubic | 103.851 | 14 | 7.418 | |||||||
Quadratic | Linear | 276.066 | 14 | 19.719 | ||||||
Quadratic | 227.784 | 14 | 16.270 | |||||||
Cubic | 173.974 | 14 | 12.427 | |||||||
method * style | Linear | Linear | 53.676 | 1 | 53.676 | 1.423 | .253 | |||
Quadratic | 372.432 | 1 | 372.432 | 4.119 | .062 | |||||
Quadratic | Linear | .394 | 1 | .394 | .013 | .911 | ||||
Quadratic | 22.509 | 1 | 22.509 | .898 | .359 | |||||
Error(method*style) | Linear | Linear | 527.999 | 14 | 37.714 | |||||
Quadratic | 1265.832 | 14 | 90.417 | |||||||
Quadratic | Linear | 421.207 | 14 | 30.086 | ||||||
Quadratic | 351.048 | 14 | 25.075 | |||||||
speaker * style | Linear | Linear | 57.543 | 1 | 57.543 | .716 | .412 | |||
Quadratic | 25.926 | 1 | 25.926 | .480 | .500 | |||||
Quadratic | Linear | 1606.556 | 1 | 1606.556 | 22.744 | .000 | ||||
Quadratic | 8.862 | 1 | 8.862 | .128 | .726 | |||||
Cubic | Linear | 693.367 | 1 | 693.367 | 5.567 | .033 | ||||
Quadratic | 7.469 | 1 | 7.469 | .128 | .726 | |||||
Error(speaker*style) | Linear | Linear | 1125.785 | 14 | 80.413 | |||||
Quadratic | 756.737 | 14 | 54.053 | |||||||
Quadratic | Linear | 988.915 | 14 | 70.637 | ||||||
Quadratic | 971.889 | 14 | 69.421 | |||||||
Cubic | Linear | 1743.729 | 14 | 124.552 | ||||||
Quadratic | 819.012 | 14 | 58.501 | |||||||
method * speaker * style | Linear | Linear | Linear | 10.862 | 1 | 10.862 | .707 | .414 | ||
Quadratic | 46.051 | 1 | 46.051 | 1.464 | .246 | |||||
Quadratic | Linear | 7.764 | 1 | 7.764 | .612 | .447 | ||||
Quadratic | 30.766 | 1 | 30.766 | 1.769 | .205 | |||||
Cubic | Linear | 71.297 | 1 | 71.297 | 4.591 | .050 | ||||
Quadratic | 68.017 | 1 | 68.017 | 6.556 | .023 | |||||
Quadratic | Linear | Linear | 100.056 | 1 | 100.056 | 2.031 | .176 | |||
Quadratic | 126.714 | 1 | 126.714 | 14.617 | .002 | |||||
Quadratic | Linear | 41.328 | 1 | 41.328 | 2.008 | .178 | ||||
Quadratic | 95.775 | 1 | 95.775 | 7.947 | .014 | |||||
Cubic | Linear | 1.514 | 1 | 1.514 | .085 | .775 | ||||
Quadratic | 30.489 | 1 | 30.489 | 3.864 | .069 | |||||
Error(method*speaker*style) | Linear | Linear | Linear | 214.939 | 14 | 15.353 | ||||
Quadratic | 440.456 | 14 | 31.461 | |||||||
Quadratic | Linear | 177.502 | 14 | 12.679 | ||||||
Quadratic | 243.478 | 14 | 17.391 | |||||||
Cubic | Linear | 217.413 | 14 | 15.530 | ||||||
Quadratic | 145.248 | 14 | 10.375 | |||||||
Quadratic | Linear | Linear | 689.560 | 14 | 49.254 | |||||
Quadratic | 121.364 | 14 | 8.669 | |||||||
Quadratic | Linear | 288.140 | 14 | 20.581 | ||||||
Quadratic | 168.734 | 14 | 12.052 | |||||||
Cubic | Linear | 249.082 | 14 | 17.792 | ||||||
Quadratic | 110.472 | 14 | 7.891 | |||||||
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Source | Type III Sum of Squares | df | Mean Square | F | Sig. | ||||
Intercept | 640563.338 | 1 | 640563.338 | 110.932 | .000 | ||||
Error | 80840.966 | 14 | 5774.355 | ||||||
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method | Mean | Std. Error | 95% Confidence Interval | |||
Lower Bound | Upper Bound | |||||
1 | 37.683 | 3.401 | 30.388 | 44.979 | ||
2 | 33.840 | 3.257 | 26.854 | 40.826 | ||
3 | 31.802 | 3.518 | 24.256 | 39.348 | ||
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(I) method | (J) method | Mean Difference (I-J) | Std. Error | Sig.b | 95% Confidence Interval for Differenceb | |||
Lower Bound | Upper Bound | |||||||
1 | 2 | 3.844* | 1.086 | .010 | .892 | 6.795 | ||
3 | 5.881* | 1.539 | .006 | 1.698 | 10.065 | |||
2 | 1 | -3.844* | 1.086 | .010 | -6.795 | -.892 | ||
3 | 2.038 | 1.971 | .956 | -3.319 | 7.395 | |||
3 | 1 | -5.881* | 1.539 | .006 | -10.065 | -1.698 | ||
2 | -2.038 | 1.971 | .956 | -7.395 | 3.319 | |||
Based on estimated marginal means | ||||||||
*. The mean difference is significant at the | ||||||||
b. Adjustment for multiple comparisons: Bonferroni. | ||||||||
Value | F | Hypothesis df | Error df | Sig. | |
Pillai's trace | .683 | 14.005a | 2.000 | 13.000 | .001 |
Wilks' lambda | .317 | 14.005a | 2.000 | 13.000 | .001 |
Hotelling's trace | 2.155 | 14.005a | 2.000 | 13.000 | .001 |
Roy's largest root | 2.155 | 14.005a | 2.000 | 13.000 | .001 |
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 | |||||
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speaker | Mean | Std. Error | 95% Confidence Interval | |||
Lower Bound | Upper Bound | |||||
1 | 40.341 | 3.828 | 32.131 | 48.550 | ||
2 | 32.532 | 3.406 | 25.227 | 39.838 | ||
3 | 30.026 | 3.166 | 23.236 | 36.816 | ||
4 | 34.868 | 3.358 | 27.666 | 42.070 | ||
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(I) speaker | (J) speaker | Mean Difference (I-J) | Std. Error | Sig.b | 95% Confidence Interval for Differenceb | |||
Lower Bound | Upper Bound | |||||||
1 | 2 | 7.809* | 1.922 | .007 | 1.909 | 13.708 | ||
3 | 10.315* | 2.263 | .003 | 3.369 | 17.260 | |||
4 | 5.473 | 1.893 | .071 | -.336 | 11.282 | |||
2 | 1 | -7.809* | 1.922 | .007 | -13.708 | -1.909 | ||
3 | 2.506 | 1.471 | .663 | -2.007 | 7.019 | |||
4 | -2.336 | 1.549 | .923 | -7.091 | 2.419 | |||
3 | 1 | -10.315* | 2.263 | .003 | -17.260 | -3.369 | ||
2 | -2.506 | 1.471 | .663 | -7.019 | 2.007 | |||
4 | -4.842* | 1.464 | .031 | -9.334 | -.350 | |||
4 | 1 | -5.473 | 1.893 | .071 | -11.282 | .336 | ||
2 | 2.336 | 1.549 | .923 | -2.419 | 7.091 | |||
3 | 4.842* | 1.464 | .031 | .350 | 9.334 | |||
Based on estimated marginal means | ||||||||
*. The mean difference is significant at the | ||||||||
b. Adjustment for multiple comparisons: Bonferroni. | ||||||||
Value | F | Hypothesis df | Error df | Sig. | |
Pillai's trace | .620 | 6.533a | 3.000 | 12.000 | .007 |
Wilks' lambda | .380 | 6.533a | 3.000 | 12.000 | .007 |
Hotelling's trace | 1.633 | 6.533a | 3.000 | 12.000 | .007 |
Roy's largest root | 1.633 | 6.533a | 3.000 | 12.000 | .007 |
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 | |||||
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style | Mean | Std. Error | 95% Confidence Interval | |||
Lower Bound | Upper Bound | |||||
1 | 38.023 | 3.656 | 30.182 | 45.865 | ||
2 | 40.274 | 3.753 | 32.225 | 48.323 | ||
3 | 25.028 | 3.000 | 18.593 | 31.462 | ||
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(I) style | (J) style | Mean Difference (I-J) | Std. Error | Sig.b | 95% Confidence Interval for Differenceb | |||
Lower Bound | Upper Bound | |||||||
1 | 2 | -2.251 | 1.181 | .232 | -5.462 | .960 | ||
3 | 12.995* | 2.433 | .000 | 6.382 | 19.608 | |||
2 | 1 | 2.251 | 1.181 | .232 | -.960 | 5.462 | ||
3 | 15.246* | 2.408 | .000 | 8.703 | 21.790 | |||
3 | 1 | -12.995* | 2.433 | .000 | -19.608 | -6.382 | ||
2 | -15.246* | 2.408 | .000 | -21.790 | -8.703 | |||
Based on estimated marginal means | ||||||||
*. The mean difference is significant at the | ||||||||
b. Adjustment for multiple comparisons: Bonferroni. | ||||||||
Value | F | Hypothesis df | Error df | Sig. | |
Pillai's trace | .742 | 18.734a | 2.000 | 13.000 | .000 |
Wilks' lambda | .258 | 18.734a | 2.000 | 13.000 | .000 |
Hotelling's trace | 2.882 | 18.734a | 2.000 | 13.000 | .000 |
Roy's largest root | 2.882 | 18.734a | 2.000 | 13.000 | .000 |
Each F tests the multivariate effect of style. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means. | |||||
a. Exact statistic | |||||
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method | speaker | Mean | Std. Error | 95% Confidence Interval | |||
Lower Bound | Upper Bound | ||||||
1 | 1 | 47.089 | 4.085 | 38.327 | 55.851 | ||
2 | 35.452 | 3.519 | 27.904 | 43.000 | |||
3 | 31.959 | 3.321 | 24.837 | 39.082 | |||
4 | 36.233 | 3.547 | 28.626 | 43.841 | |||
2 | 1 | 42.578 | 4.073 | 33.843 | 51.313 | ||
2 | 30.952 | 3.340 | 23.789 | 38.115 | |||
3 | 28.200 | 3.330 | 21.058 | 35.342 | |||
4 | 33.630 | 3.154 | 26.865 | 40.394 | |||
3 | 1 | 31.356 | 3.878 | 23.037 | 39.674 | ||
2 | 31.193 | 3.682 | 23.296 | 39.089 | |||
3 | 29.919 | 3.393 | 22.641 | 37.196 | |||
4 | 34.741 | 3.748 | 26.702 | 42.780 | |||
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method | style | Mean | Std. Error | 95% Confidence Interval | |||
Lower Bound | Upper Bound | ||||||
1 | 1 | 41.097 | 3.978 | 32.565 | 49.630 | ||
2 | 44.750 | 3.950 | 36.278 | 53.222 | |||
3 | 27.203 | 3.021 | 20.724 | 33.682 | |||
2 | 1 | 37.264 | 3.490 | 29.779 | 44.749 | ||
2 | 40.081 | 3.899 | 31.717 | 48.444 | |||
3 | 24.175 | 2.996 | 17.749 | 30.601 | |||
3 | 1 | 35.708 | 3.895 | 27.355 | 44.061 | ||
2 | 35.992 | 4.176 | 27.034 | 44.949 | |||
3 | 23.706 | 3.212 | 16.817 | 30.594 | |||
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speaker | style | Mean | Std. Error | 95% Confidence Interval | |||
Lower Bound | Upper Bound | ||||||
1 | 1 | 45.870 | 4.154 | 36.962 | 54.779 | ||
2 | 46.333 | 4.654 | 36.350 | 56.316 | |||
3 | 28.819 | 3.369 | 21.594 | 36.043 | |||
2 | 1 | 35.770 | 3.708 | 27.817 | 43.724 | ||
2 | 38.907 | 3.882 | 30.582 | 47.233 | |||
3 | 22.919 | 3.672 | 15.043 | 30.794 | |||
3 | 1 | 29.544 | 3.923 | 21.131 | 37.958 | ||
2 | 35.678 | 3.388 | 28.412 | 42.944 | |||
3 | 24.856 | 3.288 | 17.803 | 31.908 | |||
4 | 1 | 40.907 | 4.181 | 31.941 | 49.874 | ||
2 | 40.178 | 3.738 | 32.161 | 48.195 | |||
3 | 23.519 | 2.935 | 17.225 | 29.813 | |||
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method | speaker | style | Mean | Std. Error | 95% Confidence Interval | |||
Lower Bound | Upper Bound | |||||||
1 | 1 | 1 | 52.133 | 4.437 | 42.617 | 61.650 | ||
2 | 53.956 | 4.963 | 43.312 | 64.599 | ||||
3 | 35.178 | 3.543 | 27.579 | 42.776 | ||||
2 | 1 | 38.600 | 4.283 | 29.415 | 47.785 | |||
2 | 44.222 | 4.093 | 35.444 | 53.001 | ||||
3 | 23.533 | 3.654 | 15.695 | 31.371 | ||||
3 | 1 | 31.344 | 4.420 | 21.866 | 40.823 | |||
2 | 37.700 | 3.709 | 29.744 | 45.656 | ||||
3 | 26.833 | 3.430 | 19.477 | 34.189 | ||||
4 | 1 | 42.311 | 4.543 | 32.567 | 52.055 | |||
2 | 43.122 | 3.917 | 34.722 | 51.523 | ||||
3 | 23.267 | 3.151 | 16.508 | 30.025 | ||||
2 | 1 | 1 | 48.211 | 4.678 | 38.177 | 58.245 | ||
2 | 51.333 | 5.182 | 40.218 | 62.448 | ||||
3 | 28.189 | 3.722 | 20.207 | 36.171 | ||||
2 | 1 | 34.533 | 3.521 | 26.982 | 42.085 | |||
2 | 36.689 | 3.891 | 28.344 | 45.034 | ||||
3 | 21.633 | 3.768 | 13.552 | 29.715 | ||||
3 | 1 | 26.944 | 3.692 | 19.026 | 34.863 | |||
2 | 33.622 | 3.765 | 25.547 | 41.697 | ||||
3 | 24.033 | 3.570 | 16.376 | 31.691 | ||||
4 | 1 | 39.367 | 3.838 | 31.134 | 47.599 | |||
2 | 38.678 | 3.732 | 30.673 | 46.683 | ||||
3 | 22.844 | 2.890 | 16.645 | 29.044 | ||||
3 | 1 | 1 | 37.267 | 4.376 | 27.880 | 46.653 | ||
2 | 33.711 | 4.458 | 24.150 | 43.272 | ||||
3 | 23.089 | 3.845 | 14.843 | 31.335 | ||||
2 | 1 | 34.178 | 3.896 | 25.822 | 42.533 | |||
2 | 35.811 | 4.523 | 26.110 | 45.512 | ||||
3 | 23.589 | 3.730 | 15.590 | 31.588 | ||||
3 | 1 | 30.344 | 3.913 | 21.951 | 38.737 | |||
2 | 35.711 | 3.984 | 27.166 | 44.256 | ||||
3 | 23.700 | 3.491 | 16.213 | 31.187 | ||||
4 | 1 | 41.044 | 4.694 | 30.976 | 51.113 | |||
2 | 38.733 | 4.539 | 28.998 | 48.468 | ||||
3 | 24.444 | 3.019 | 17.969 | 30.920 | ||||
The IBM SPSS Web Report is an interactive report that can be opened in a browser and contains charts, tables, and other output produced by IBM SPSS Statistics. Since this document is a single file, it can be placed on any web site without requiring special servers or setup, posted on a shared file server, copied onto portable file media, or distributed via email. Web Reports are HTML5 files that can be opened on all of the latest versions of the most commonly used browsers.
Web Report controls are disabled by the system. The browser you are using has JavaScript disabled or JavaScript is disabled by the system as a security measure. Without JavaScript, the report contains all of the same charts, tables and other objects as the full featured version, but the interactive features are not available. Check the settings for your browser to turn on JavaScript or try to open the report in a different browser. On a tablet or smart phone, you may need to install an HTML viewer application.
You can use the Edit toolbar to modify the appearance of tables, including changing font attributes, background color, and number of decimal positions. You can also apply a TableLook to the entire table and transpose rows and columns. You cannot change data values in the table or edit objects other than tables.
Print. Prints the entire contents of the Web Report.
Open in Simplified View. Displays the entire contents of the Web Report in a simplified view. Instead of just displaying the select output object, all contents are displayed. You can change layers in multi-dimensional tables, but you cannot make any other changes to the table.