Cesuras: Nos vs Otros

Designed by Spear, the box-and-whisker plot was originally called a range barl. Tukey later modified the display and named it box-and-whisker2, which is now commonly called as ‘box-and-whisker plot’ or simply ‘box plot’23. A box-and-whisker plot is a visual representation of how the data is spread out and how much variation there is. Box and whisker plots are considered an excellent tool for conveying location and variation information in data sets, especially for detecting and illustrating location and variation changes between different groups of data (Chambers et al., 1983). The plots allow researchers to explore the data and to draw informal conclusions when two or more variables are present. The main advantage of the box-and-whisker plot is that it is not cluttered by showing all the data values. It only highlights the important features of the data. It indicates skewedness24 and highlights unusual distributions. A box plot (as it is often called) is especially helpful for indicating skewness and highlighting unusual observations (outlier25) in the data set. The box-and-whisker plot, therefore, makes it easier to focus attention on the median, extremes, and quartiles and comparisons among them.26

Figure 3.1 illustrates how the distribution of the difference in mean scores (DIFFMEAN) of the responses of the judges varies by both gender and observer language group (obr_language). By looking at this box-and-whisker plot we can tell a

23 www.qualitvdigest.com/oct97/html/excel.html. 05.10.2004.

24 Skewness is defined as asymmetry in the distribution o f the sample data values. Values on one side of the distribution tend to be further from the 'middle' than values on the other side.

25An outlier is an observation in a data set which is far removed in value from the others in the same data set. It is an unusually large or an unusually small value compared to the others.

m ore coherent story from this exploratory analysis all the way through m ore formal analysis. This descriptive view o f the data gives an evidence o f the effect o f gender and speech group on the evaluations o f 'b o th ’ the speakers.

o.o -

a

i f i

Siraiki

GEN1

F ig u re 3. 1 Box-and-whisker plot o f gender and observer language groups

In Figure 3.1 each plot com prises a shaded box and two whiskers; represented by two vertical lines connecting the box to two horizontal lines. The horizontal lines o f the w hiskers indicate the m inim um and m axim um values, e.g. GEN 1= M, observer language= Siraiki, the box-and-w hisker plot tells us that the m inim um difference in m eans is approxim ately zero, while the m axim um difference in m eans is ju st above 1.

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The length o f the vertical lines correspond to the upper quartiles, i.e. the interval caused by the highest 25% o f values, and the low er quartile i.e. the interval caused by 27 Quartiles are values that divide a sample o f data into four groups containing (as far as possible) equal numbers o f observations.

the lowest 25% of values, e.g. in GEN 1= M, obr_language= Siraiki, the upper covers interval (1.0, 1.1) while the lower quartile covers interval (0.1, 0.5). The horizontal line within the shaded box represents the median (or middle) value, e.g. GEN 1= M and obr_language = Siraiki, the median difference in means is 0.6. The height of the shaded box corresponds to the interquartile range, i.e. the middle 50% of values, e.g. GEN 1= M, obr_language= Siraiki, the interquartile range covers the interval (0.5, 1.0).

The skewness in the plot in figure 3.1 is indicated by the whiskers of unequal length, e.g. our working example GEN 1= M, obr_language= Siraiki, indicates that the upper quartile is narrower than the lower quartile. The location of the horizontal line within the box may also indicate skewness within the middle quartiles. No outliers are indicated on the plots.

The dichotomy between the opinions of the Siraiki male judges and all the other judges is evident from this plot. The major difference between the Siraiki male judges and all the other judges lies in the location of the distribution, e.g. the median for the Siraiki male judges is 0.6 compared to the medians of all the other judges which lie within the interval (-1.5,-0.5). Considering only the female judges, the difference of the response of the female Siraiki judges also appears to vary from that of the Punjabi and the Urdu speaking female judges but to a lesser extent than the male judges.

This telling evidence of gender and observer language effect on the evaluations of the two speakers necessitated carrying out an analysis of variance on the data. My next step, therefore, was to confirm through ANOVA the gender and observer language effect on the evaluations, which was evident from the box-and- whisker plot.

3.2.5.iv ANOVA

As the thirteen items in the evaluation sheet could not be grouped under three categories, appropriate ANOVAs were carried out separately for the thirteen items. The two factors in this analysis were respondents’ sex and speech groups. Analysis of variance, commonly known as ANOVA, is used to uncover the main and interaction effects of categorical variables, called factors, on an internal dependent variable. The chief statistic in ANOVA is the F-test of difference of group means which tests whether the means of the groups formed by values of the factors (also called independent variables) or the combinations of the values for multiple factors or independent variables are different enough not to have occurred by chance. If the analysis shows that the group means do not differ significantly then it is deduced that the factor(s) did not have an effect on the response variable (also called dependent variable). However, if the F test yields that overall the factor(s) is (are) related to the response variable, then Post Hoc tests or Multiple Comparison Tests of significance are used to investigate which value groups of the factor(s) is (are) greatly affecting the relationship.28

In ANOVA a ‘main effect’ is defined as the direct effect of the factor on the response variable. Main effects are the unique effects of the categorical independent variables. If the probability of F is less than 0.05 for any independent variable then it is inferred that the variable does not have an effect on the dependent variable. An ‘interaction effect’ is the combined or joint effect called ‘interaction’ of two or more factors on the response variable. When there is interaction, the effect of a factor on response variable varies according to the values of the other factor. If the probability

of F is less than 0.05 for any such combinations then it is concluded that the interaction of the combination has an effect on the response variable.

The ANOVA results show significant gender and/or observer language effect on the difference in the evaluation in eleven items out of thirteen. Only in item thirteen (Handsome—Not Handsome), gender, observer language as well as the interaction of these factors has a significant effect on the difference of the evaluation of the speakers by the judges. These results necessitated post-hoc tests on items which showed a significant observer language effect. Post-hoc tests cannot be performed on the gender factor because these are fewer than three groups. The results of these analyses are discussed below.

In item one (educated—uneducated) and two (intelligent—unintelligent) the results indicate that in comparison with the Urdu speaker the Siraiki speaker is judged negatively (cf. table 3.2). The ANOVA results suggest that gender is significantly affecting the difference in evaluation with F (1,24) = 10.622, P = 0.003 in item one and with F (1,24) = 4.841, P = 0.038 in item two. Furthermore, the means suggest that female judges, compared with the male judges are evaluating the Siraiki speaker more negatively. In other words, the female judges compared with their male counterparts, have a lower opinion of the Siraiki speaker on the dimensions of education and intelligence.

In item five (competent—incompetent), it is the observer language factor which is significantly affecting the difference in the evaluation of the two speakers with F (2, 24) = 15.087, P = 0.000. Observer language refers to the grouping of the judges according to their speech groups which are Siraiki, Punjabi and Urdu. The judges belonging to all speech groups have evaluated the Siraiki speaker negatively in

comparison with the Urdu speaker. Punjabi judges have given the most negative rating to the Siraiki speaker, after them the Urdu speaking judges and then the Siraiki judges. The results of the post-hoc test for this item reveal that in the pair-wise comparisons, there is a significant difference between the ratings given by the Punjabi and the Siraiki judges but not between the Punjabi and the Urdu-speaking judges. The variation between the opinions of the Siraiki and the Urdu-speaking judges is also significant.

In contrast to what we have observed so far, for item six (kind—unkind) the evaluation has reversed. Here the Siraiki speaker has been rated positively in comparison with the Urdu speaker. For this item, both gender and observer language factors significantly affect the difference in the evaluation of both the speakers with F (1,24) = 5.309, P = 0.030 and F (2,24) = 5.644, P = 0.010 respectively. Compared to the female judges, the male judges have evaluated the Siraiki speaker more positively on this scale. For the observer language factor, among the three groups of the judges, the Siraiki judges have given the most positive rating to the Siraiki speaker followed by the ratings given by the Punjabi and the Urdu-speaking judges. The results of the post-hoc test of this factor illustrate that the difference between the ratings given by the Siraiki and the Urdu-speaking judges is significant. The difference in the evaluation given by the Siraiki judges in comparison with the Punjabi judges is also significant.

In item 7 (sincere—insincere), again it is the Siraiki speaker who is rated positively in comparison with the Urdu speaker and here only the observer language factor significantly affects the difference in the evaluations with F (2,24) = 4.107, P = 0.029. The results show the same pattern as we saw for item 6. The Siraiki group of judges have given the most positive rating to the Siraiki speaker followed by the

ratings given by the Punjabi and then the Urdu-speaking judges. The results of the post-hoc test for observer language effect also reveal the similar results as we saw for item six.

In items eight (humble—arrogant) and nine (dependable—undependable) in which the Siraiki speaker has been judged more positively, the gender factor significantly affects the evaluations with F (1,24) = 5.303, P = 0.030 for item eight and F (1,24) = 8.351, P = 0.008 for item nine. In both the items, compared to the female judges, the male judges have given a better rating to the Siraiki speaker.

In items ten (friendly—unfriendly), eleven (pleasant—unpleasant) and twelve (polite—impolite), the Siraiki speaker has been evaluated negatively in comparison to the Urdu speaker. The gender factor, across all these items, significantly affects the difference in the evaluations of the judges with F (1,24) = 8.666, P = 0.007, F (1,24) = 4.536, P = 0.044 and, F (1,24) = 7.694, P = 0.011 for items ten, eleven and twelve, respectively. In each case the evaluation of the Siraiki speaker by the female judges is more negative as compared to the one given by the male judges.

Item 13 is the only scale in which the difference in the evaluation of the speakers is significantly affected by gender with F (1,24) = 12.300, P = 0.002, observer language with F (2,24) = 3.676, P = 0.040, as well as the interaction between gender and observer language with F (2,24) = 6.293, P = 0.006. The Siraiki speaker in this scale is evaluated negatively in comparison with the Urdu speaker. For the gender factor, the female judges have evaluated the Siraiki speaker more negatively in comparison with their male counterparts. Among the three groups of judges, the Punjabi judges have given the most negative evaluation of the Siraiki speaker. The second most negative rating is given by the Urdu-speaking judges followed by the

rating given by the Siraiki judges. The results o f the post-hoc test reveal that am ong the pair-w ise com parisons, only the difference betw een the ratings given by the Punjabi and the Siraiki judges is significant.

The interaction betw een gender and the observer language is illustrated in the follow ing line chart2 .

Estimated Marginal Means of MEANS

1.5 1.0 .5 0.0 .5 ,O BSLANG -1.0 -1.5 -2.0 - 2 5 F M G E N D E R

F ig u re 3. 2 Line chart o f interaction between gender and observer language effect for item thirteen

Figure 3.2, the graphic representation o f the interaction illustrates the com bined effect o f the gender and observer language factors w hich are significantly affecting the difference in the evaluation o f the Siraiki and the Urdu speaker. In this figure the lines representing the gender effect for the Punjabi and the Urdu speaking judges are parallel to each other which m eans that the gender effects for these two groups o f ju d g es are sim ilar. How ever, the line representing the gender effect for the Siraiki ju d g es is clearly not parallel to the other two lines. Indeed the slope o f this

29 Line charts contain more data than do the other types o f charts. In these charts m ultiple lines can be plotted to provide com parison and trends o f two data values over the same time period.

third line is steeper. This third line crosses the other two lines which indicates that the gender effect for the Siraiki judges is markedly different from gender effects of the other judges.