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Table 2 Dimension by Exercise Matrix

in unknown title
by unknown authors
"... In PAGE 5: ... Ratings were combined using a complex multistage clinical integration process. This essentially involved reaching agreement initially over the combined rating for each candidate on each dimension by exercise, as per the targeted matrix given in Table2 . Assessors then discussed and agreed on a com- bined rating by dimension across all exercises measuring that particular dimension, most commonly equating to a rough mean rating by dimension (see Goffin, Rothstein, amp; Johnston, 1996).... In PAGE 9: ... As noted above, the latent mean analyses did find significant differences in favor of men on two latent exercise factors (planning exercise and other command tasks). As shown in Table2 , problem solving is measured in one of these exercises, namely the other command tasks. So, the gender difference on the observed dimension of problem solving is not really a gender difference on the latent construct of problem solving.... ..."

Table 3 Student Design Performance by Gender Male Female

in Articles An Assessment Model for a Design Approach to Technological Problem Solving
by Rodney Custer Brigitte, Brigitte G. Valesey, Barry N. Burke
"... In PAGE 9: ... The complexities of these factors provide rich opportunities for additional research. Student performance was also analyzed by gender (see Table3 ). While the total scores were nearly identical, there are differences in Dimensions #3 and #4.... ..."

Table 11: Levene apos;s Test - equal variances

in PRIOR PROGRAMMING EXPERIENCE AND THE INFLUENCE IT HAS ON STUDENTS' PERFORMANCE IN AN INTRODUCTORY
by Kylie Pegg, Kylie Pegg
"... In PAGE 6: ...able 10: Test for Normality - Prior Programming Experience............................... 79 Table11 : Levene apos;s Test - equal variances.... In PAGE 89: ....3.4.2 Equality of Variance Testing To test for the equality of variance, an assumption of ANOVA, Levene apos;s test was conducted. The results of the test (see Table11 below) were not significant (p-value 0.... ..."

Table 1 Overview of Previous Published Studies of Gender Differences in Assessment Centers

in unknown title
by unknown authors
"... In PAGE 1: ... The setting of this study is a large-scale assessment center for officer entry in the British Army. Study Background The Construct-Driven Perspective in Assessment Centers A first critical limitation of most of the studies in Table1 is that gender differences were typically evaluated at the level of the OAR. Although it is clear that the OAR is of great practical importance (hiring decisions are contingent on it), it typically is a summary rating of assessor evaluations on a wide variety of dimensions (e.... In PAGE 7: ...27. For comparison reasons with prior research (see Table1 ), we also computed d associated with the OAR. Female candidates (M H11005 2.... ..."

Table 4.5 Change in Average Lateral Dimension for RSST-CH Specimens During Testing, HVS Mix.

in Context and Content
by Washington D. C, J. Harvey, I. Guada, F. Long 1999
Cited by 1

Table 2 shows the top discriminatory unigram features when a threshold T of 500 was used. A similar process has been applied to bigrams and trigrams, and sample discriminatory features are also shown in Table 2.

in Of Men, Women, and Computers: Data-Driven Gender Modeling for Improved User Interfaces Abstract
by Hugo Liu
"... In PAGE 3: ... Table2 : Top discriminatory unigram/bigram/trigram features 4. Dimensions of the gender space The perspectives of men and women are complex systems, but these complex systems may afford simple and elegant projections capa- ble of producing deft insight into what the genders share and how they differ.... ..."

Table 3: Gender classifications errors based on different speaker representation methods (The result is according to the projection of PCA, the total number for EW and SH are 500 and 480 respectively)

in Analysis of Speaker Variability
by Chao Huang Tao, Chao Huang, Tao Chen, Stan Li, Eric Chang, Jianlai Zhou
"... In PAGE 3: ... There are a total of 65 classes. Here only the offset of MLLR transformation matrix and the 26 dimensions in feature stream are used according to the results demonstrated in Table3 . The selections of different regression classes are defined in Table 4, and the corresponding gender classification results are shown in Table 5.... ..."

TABLE XII ENROLLMENT FIGURES BY GENDER Gender Enrollment

in Computer Science Education: An Information Resource For Curriculum Development And Program Enhancement
by Rene McCauley, Bill Manaris, Session Ta

Table A3: Student gender by provider Gender

in unknown title
by unknown authors

Table 8. Gender

in unknown title
by unknown authors 2004
"... In PAGE 4: ...able 7: Age Range............................................................................................ 30 Table8 : Gender.... ..."
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