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Figure 1 – uploaded by Odonchimeg Tumee
Figure 1 Results of regression analysis of RTs: inverse linearity between RTs and Word Frequency as a predictor Firstly, we examined the relation between each of the three predictors (word frequency, word length in characters and word length in syllables) and the standardized RTs (in correct responses only), expecting the increase of RTs to the words with lower frequency and greater length (inhibitory effect). As it is assumed that RT distribution generally doesn’t correspond to Gaussian distribution (McGill, 1963) we calculated a nonparametric coefficient of correlation (R for Spearman) for each pair of variables. It was not significant either for word length in characters (r,= .228, n=30, p = .225), or for word length in syllables (r= .026, n=30, p = .890). But we revealed strong negative correlation for RTs and word frequency (r= — .622, n=30, p < .0001) (Fig. 1).
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