# Do Background Colors Have an Impact on Preferences and Catch the Attention of Users?
## 4 Results
### Division into Groups  
Division into groups was computed based on the \(k\)-means clustering algorithm in Stage 3 of our algorithm (see Figure 4). The results for sustained attention are depicted in Figure 10, while those for divided attention are shown in Figure 11. It is worth noting that, independently of the attention model, the low-ranking positions belonged to the same colors: Violet, orange, and gray. This means that they should not be used in any situation where drawing attention is of particular importance. When the groups of colors were selected, the statistical significance between them was examined. We checked the data distribution and found it to be normal, and the  
Figure 11: Divided attention, assessed by user’s first impression. Top: division into groups based on the \(k\)-means clustering algorithm; Bottom: luminance for each group of colors. Although the data are discrete, the dotted line in the graph was added to emphasize the luminance differences between the corresponding colors in the ranking. Figure 10: Sustained attention, assessed by user preferences. Top: division into groups was computed based on the \(k\)-means clustering algorithm; Bottom: luminance for each group of colors. Although the data are discrete, the dotted line in the graph was added to emphasize the luminance differences between the corresponding colors in the ranking. Figure 9: Divided attention: First impression of users given in a sum of ranking positions determined for every background color (according to Table 2). variance was homogeneous; therefore, the ANOVA test with a confidence level of 90% was employed in further analysis. To exclude the influence of luminance on the experimental results and color perception by the user, luminance was calculated for each color. For each image (consisting of a primary and secondary color), a luminance value was calculated for each pixel, and these values were averaged. Figures 10 and 11 present the luminance values for all background colors, composed with pictograms colors, respectively for sustained and divided attention. The luminance results were in agreement with widespread color theory and models: the highest luminance was for the white color, and the lowest was for black. Comparing luminance charts to the color ranking, it can be expected that luminance did not have an important influence on user preferences or ET. The ranking distribution, in both cases, was different from the luminance values. **Sustained attention**. The group of colors that the users considered to be most readable and friendly was Group 1 (\(gp1\)), independent of background color, consisting of white (see Figure 12). Its result was statistically different from those for the rest of the groups; that is, black and yellow (\(gp2\)), blue/green/red (\(gp3\)), and violet/orange/gray (\(gp4\)). The group \(gp4\) attracted the user's sustained attention the worst, independent of the background color. There was no statistical difference between the results for groups \(gp2\) and \(gp3\). The \(p\)-values obtained from ANOVA test with 90% confidence level are presented in Table 3. As mentioned above, only the two middle groups (\(gp2\) and \(gp3\)) did not differ statistically significant from each other. However, in practice, when analyzing the effect size, 73% of users preferred the yellow/black group over the blue/green/red one. On the other hand, despite the statistical significance between \(gp1\) and \(gp2\), only 61% of users found the white color to be more readable and friendly than yellow/black. This means that white more strongly attracted the sustained attention of users, compared to the other colors, independent to the background color; however, yellow and black colors can be also taken into account. For the next colors--blue, green, and red--their choice in components that should attract the attention of users should be considered carefully. Taking the value of contrast between the colors and background into account could be helpful.