Part 1: Getting Started with the EQ-i 2.0 Part 2: Administering a Self-Report EQ-i 2.0 Part 3: Administering a Multirater EQ 360 2.0 Part 4: Using the Results Part 5: Creating the EQ-i 2.0 and EQ 360 2.0

Appendix D: EQ-i® 2.0 Australian Norms

This appendix presents the statistical results pertaining to the development of the Australian EQ-i 2.0 General Population Norms and EQ 360 2.0 Norms. Please see Australian Norms for full interpretive text.

print this table

Table D.1. Age × Gender Distribution of Australian EQ-i 2.0 Normative Sample

The following table presents the distribution of the Australian EQ-i 2.0 normative sample, categorised by age group and gender. An equal number of males and females were sampled at each age group.

Table D.1.

back to top

print this table

Table D.2. Geographic Region Distribution of Australian EQ-i 2.0 Normative Sample

The following table summarises the geographic region distribution of the Australian EQ-i 2.0 normative sample. Data were collected from a wide variety of geographic regions throughout Australia.

Table D.2.

back to top

print this table

Table D.3. Education Level Distribution of Australian EQ-i 2.0 Normative Sample

The following table summarises the education level (i.e., highest level of attained education) distribution of the Australian normative sample. Most applications of the EQ-i 2.0 in Australia (and in other countries) are within professional contexts, and as such most of the data was collected from individuals with higher education levels. However, to ensure the data was relevant to the general population of Australia, a percentage of the data (17.5%) was also collected from those with a lower education level.

Table D.3.

back to top

print this table

Table D.4. Multivariate Effects of Age and Gender in the EQ-i 2.0 Australian Norm Sample

The following table summarises the results from the multivariate analyses of covariance (MANCOVAs) conducted on the composite scales and subscales to examine effects of gender, age, and the interaction between gender and age on EQ-i 2.0 scores in the Australian normative sample. Wilks’ lambda ranges from 0.00 to 1.00 and depicts the amount of variance not explained by the demographic variable. F and p values convey the statistical significance of the effect. Partial η2 values provide an effect size for describing the effects as small, medium, or large. Meaningful effect sizes (i.e., partial η2 ≥ .01) suggest differences among participants based on the demographic variable.

Table D.4.

back to top

print this table

Table D.5. Effect Sizes for Gender and Age Effects in the EQ-i 2.0 Australian Norm Sample

The following table summarises the effect sizes for the effects of gender, age, and the interaction between gender and age on the EQ-i 2.0 Total EI score, composite scales, and subscales in the Australian normative sample. Meaningful effect sizes (i.e., |d| ≥ 0.20, partial η2 ≥ .01) suggest differences among participants based on the demographic variable, and that separate demographic norm groups may be required.

Table D.5.

back to top

print this table

Table D.6. Gender Differences in the EQ-i 2.0 Australian Norm Sample

The following table provides EQ-i 2.0 standard score scale means and standard deviations for males and females in the Australian normative sample. F and p values convey the statistical significance of gender differences; p values lower than .01, which were found for several scales, indicate significant differences between males and females.

Table D.6.

back to top

print this table

Table D.7. Age Differences in the EQ-i 2.0 Australian Norm Sample

The following table provides EQ-i 2.0 standard score scale means and standard deviations for the various age groups in the Australian normative sample. F and p values convey the statistical significance of age group differences; p values lower than .01, which were found for all scales, suggest significant differences among the age groups.

Table D.7.

back to top

print this table

Figure D.1. Histogram of EQ-i 2.0 Total EI Standard Scores in the Australian Normative Sample

This figure illustrates the distribution of EQ-i 2.0 Total EI standard scores in the Australian normative sample. The distribution of the actual scores closely approximates the normal “bell-shaped” curve (shown using the black curved line), which suggests that it is unnecessary to apply a normalising transformation to the scores. Distributions for the other composite scales and subscales show a similar pattern.

Figure D.1.

back to top

print this table

Table D.8. Australian General Population Norm Sample Scored with North American General Population Norms

The following table provides EQ-i 2.0 standard score scale means and standard deviations for the Australian normative sample when scored with the North American norms, and compared against a mean of 100. Cohen’s d values provide an effect size to describe differences between the samples as small, medium, or large; t and p values provide statistical significance tests for these differences.

Table D.8.

back to top

print this table

Table D.9. Internal Consistency of EQ-i 2.0 Scales in the Australian Norm Sample

The following table summarises the internal consistency (Cronbach’s alpha) values for the EQ-i 2.0 scales in the Australian normative sample, presented overall and separately by age and gender norm group. Alpha values range from 0.00 to 1.00. Higher values, like those found in the Australian normative sample, provide evidence for strong reliability.

Table D.9.

back to top

print this table

Table D.10. Correlations Among EQ-i 2.0 Composite Scales in the Australian Norm Sample

The following table illustrates the correlations among the EQ-i 2.0 composite scales in the Australian normative sample. Correlations range from 0.00 to 1.00, with higher values suggesting the scales are interrelated and measure a common construct (i.e., emotional intelligence). Very high values (e.g., > .90) would suggest a unidimensional factor structure. Moderate to large sized correlations, like those found in the Australian normative sample, support both the concept that the scales measure an underlying common construct, as well as the multidimensional factor structure of the EQ-i 2.0.

Table D.10.

back to top

print this table

Table D.11. Correlations Among EQ-i 2.0 Subscales in the Australian Norm Sample

The following table illustrates the correlations among the EQ-i 2.0 subscales in the Australian normative sample. Correlations range from 0.00 to 1.00, with higher values suggesting the scales share a relevant common psychological characteristic. Shaded cells indicate correlations between subscales within the same composite scale. Moderate correlations were found within the composite scales, supporting both the concept that the scales measure a common psychological characteristic, as well as the multidimensional factor structure of the EQ-i 2.0.

Table D.11.

back to top

print this table

EQ 360 Australian Norms

Table D.12. Length of Rater/Ratee Relationship in Australian EQ 360 2.0 Normative Sample

The following table describes the raters in the Australian EQ 360 2.0 normative sample in terms of the length of their relationship with the ratee. To ensure that raters had known the ratees long enough to have adequate knowledge about them, raters who knew ratees for less than 3 months were excluded from the sample. The majority of raters (86.1%) indicated that they knew the ratee for at least one year.

Table D.12.

back to top

print this table

Table D.13. Strength of Rater/Ratee Relationship in Australian EQ 360 2.0 Normative Sample

The following table describes the raters in the Australian EQ 360 2.0 normative sample in terms of the strength of their relationship with the ratee. To ensure that raters had adequate knowledge about the ratees, raters who responded “Not Very Well” to the item about how well they know the ratee were excluded from the sample. All raters, therefore, knew the person they were rating at least “Fairly Well.”

Table D.13.

back to top

print this table

Table D.14. Frequency of Rater/Ratee Interactions in Australian EQ 360 2.0 Normative Sample

The following table describes the raters in the Australian EQ 360 2.0 normative sample in terms of the frequency of interaction with the ratee. Raters indicated interaction on a regular basis with the ratee, which means the ratings are well-informed.

Table D.14.

back to top

print this table

Table D.15. Ratee Age Group by Gender Distribution in the Australian EQ 360 2.0 Normative Sample

The following table describes the gender distribution of the Australian EQ 360 2.0 normative sample within age groups. Proportions are similar across gender and age groups.

Table D.15.

back to top

print this table

Table D.16. Distribution of Ratee Gender and Age Group by Rater Type in the Australian EQ 360 2.0 Normative Sample

The following table describes the gender and age group distribution of ratees in the Australian EQ 360 2.0 normative sample within each rater type.

Table D.16.

back to top

print this table

Table D.17. Distribution of Ratee Geographic Region in the Australian EQ 360 2.0 Normative Sample

The following table summarises the geographic region distribution of the Australian EQ 360 2.0 normative sample, along with Census information. Percentages for all regions match Census proportions within 2%, suggesting the normative data can be used to effectively represent the general population of Australia.

Table D.17.

back to top

print this table

Table D.18. Multivariate Effects of Ratee Age, Gender, and Rater Type on EQ 360 2.0 Scores in the Australian Norm Sample

The following table summarises the results from the multivariate analyses of variance (MANOVAs) conducted on the EQ 360 2.0 composite scales and subscales to examine effects of gender, age, and rater type, and the interactions between these variables in the Australian normative sample. Wilks’ lambda ranges from 0.00 to 1.00 and depicts the amount of variance not explained by the demographic variable. F and p values convey the statistical significance of the effect. Partial η2 values provide an effect size for describing the effects as small, medium, or large. Meaningful effect sizes (i.e., partial η2 ≥ .01) suggest differences among participants based on the demographic variable.

Table D.18.

back to top

print this table

Table D.19. Effect Sizes for Gender, Age, and Rater Type Effects in the Australian EQ 360 2.0 Norm Sample

The following table summarises the effect sizes for the effects of the ratee’s gender, ratee’s age, and rater type on the EQ 360 2.0 Total EI score, composite scales, and subscales in the Australian normative sample. The d and partial η2 values found in the Australian EQ 360 2.0 normative sample suggest negligible or very small effects of the ratee’s gender, ratee’s age, and rater type. This result means that there is no need to have separate age and gender norms for the EQ 360 2.0.

Table D.19.

back to top

print this table

Table D.20. Ratee Gender Differences in EQ 360 2.0 Scores in the Australian Norm Sample

The following table provides EQ 360 2.0 standard score scale means and standard deviations for males and females in the Australian normative sample. F and p values convey the statistical significance of gender differences; although some results were statistically significant (p values lower than .01), this was due to the large sample sizes, and the effect sizes were negligible for most scales (see Table D.19).

Table D.20.

back to top

print this table

Table D.21. Ratee Age Differences in EQ 360 2.0 Scores in the Australian Norm Sample

The following table provides EQ 360 2.0 standard score scale means and standard deviations for the various age groups in the Australian normative sample. F and p values convey the statistical significance of age group differences; although some results were statistically significant (p values lower than .01), this was due to the large sample sizes, and the effect sizes were negligible for most scales (see Table D.19).

Table D.21.

back to top

print this table

Table D.22. Rater Type Differences in EQ 360 2.0 Scores in the Australian Norm Sample

The following table provides EQ 360 2.0 scale means and standard deviations for the various rater types in the Australian normative sample. F and p values convey the statistical significance of rater type group differences; although some results were statistically significant (p values lower than .01), this was due to the large sample sizes, and the effect sizes were negligible for most scales (see Table D.19).

Table D.22.

back to top

print this table

Figure D.2. Histogram of EQ 360 2.0 Total EI Standard Scores in the Australian Norm Sample

This figure illustrates the distribution of EQ 360 2.0 Total EI standard scores in the Australian normative sample. The distribution of the actual scores closely approximates the normal “bell-shaped” curve (shown using the black curved line), which suggests that it is unnecessary to apply a normalising transformation to the scores. Distributions for the other composite scales and subscales show a similar pattern.

Figure D.2.

back to top

print this table

Table D.23. Australian EQ 360 2.0 General Population Norm Sample Scored with North American General Population Norms

The following table provides EQ 360 2.0 standard score scale means and standard deviations for the Australian normative sample when scored with the North American EQ 360 2.0 norms, and compared against a mean of 100. Cohen’s d values provide an effect size to describe differences between the samples as small, medium, or large; t and p values provide statistical significance tests for these differences. The results indicate negligible differences between EQ 360 2.0 scores obtained from the Australian general population norm sample and the North American EQ 360 2.0 general population norms.

Table D.23.

back to top

print this table

Table D.24. Internal Consistency of EQ 360 2.0 Scales in the Australian Norm Sample

The following table summarises the internal consistency (Cronbach’s alpha) values for the EQ 360 2.0 scales in the Australian normative sample. Alpha values range from 0.00 to 1.00. Higher values, as found in the Australian normative sample, provide evidence for the strong reliability of the EQ 360 2.0.

Table D.24.

back to top

print this table

Table D.25. Correlations among EQ 360 2.0 Composite Scales in the Australian Norm Sample

The following table illustrates the correlations among the EQ 360 2.0 composite scales in the Australian normative sample. Correlations range from 0.00 to 1.00, with higher values suggesting the scales are interrelated and measure a common construct (i.e., emotional intelligence). Very high values (e.g., > .90) would suggest a unidimensional factor structure. Moderate to large sized correlations, like those found in the Australian normative sample, support both the concept that the scales measure an underlying common construct, as well as the multidimensional factor structure of the EQ 360 2.0.

Table D.25.

back to top

print this table

Table D.26. Correlations Among EQ 360 2.0 Subscales in the Australian EQ 360 2.0 Norm Sample

The following table illustrates the correlations among the EQ 360 2.0 subscales in the Australian normative sample. Correlations range from 0.00 to 1.00, with higher values suggesting the scales share a relevant common psychological characteristic. Shaded cells indicate correlations between subscales within the same composite scale. Moderate correlations were found within the composite scales, supporting the multidimensional factor structure of the EQ 360 2.0.

Table D.26.

back to top

References Appendices Publisher's Preface About the Originator Acknowledgements