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Knowledge of Statistics or Statistical Learning? Readers Prioritize the Statistics of their Native Language Over the Learning of Local Regularities Cover

Knowledge of Statistics or Statistical Learning? Readers Prioritize the Statistics of their Native Language Over the Learning of Local Regularities

Open Access
|Feb 2022

Figures & Tables

joc-5-1-209-g1.png
Figure 1

Experiments 1–2: Density plots illustrating average bigram frequency (ABF), minimal bigram frequency (minBF), and maximal bigram frequency (maxBF) for fictitious words, foils, and real words in the Italian lexicon.

joc-5-1-209-g2.png
Figure 2

Experiments 1–2: An illustration of how average bigram frequency (ABF), minimal bigram frequency (minBF), and maximal bigram frequency (maxBF) were calculated. For each of the novel strings (e.g., etesse), we identified all bigrams present in this string and matched them with the frequencies with which these bigrams occur in the Italian lexicon (SUBTLEX-IT; Crepaldi et al., 2015; Italian bigram frequencies were calculated as position-independent occurrence probabilities). ABF was defined as the average value of the frequencies of all the bigrams present in that string, minBF was equivalent to the frequency of the bigram with the lowest frequency from all the bigrams present in this string (e.g., f[ss] = 0.0055), and maxBF was equivalent to the frequency of the bigram with the highest frequency (e.g., f[e ] = 0.0212).

Table 1

Experiments 1–2: A correlation matrix (Spearman’s ρ; all ps < .01) illustrating the similarity in letter and bigram probabilities as calculated based on fictitious word strings, foils, and the Italian lexicon.

EXPERIMENT 1
ITALIANWORDSFOILS
letter probabilitiesItalian0.970.91
words0.970.92
foils0.910.92
bigram probabilitiesItalian0.780.43
words0.780.37
foils0.430.37
EXPERIMENT 2
ITALIANWORDSFOILS
letter probabilitiesItalian0.960.86
words0.960.86
foils0.860.86
bigram probabilitiesItalian0.840.35
words0.840.28
foils0.350.28
joc-5-1-209-g3.png
Figure 3

Experiments 1–2: Mean percentages of “word” responses for each item, shown by Type (foil vs. word strings) and Seen (previously unseen vs. seen). The fitted lines represent the effect of minimal bigram frequency (minBF).

Table 2

Experiments 1–2: Results from the fixed effects structure of the GLMM’s including ABF, minBF, Type (foil vs. word) and Seen (unseen vs. seen).

EXPERIMENT 1
β^SEzp
Intercept.06.09.67.504
ABF.06.07.92.356
Type–.04.08–.50.620
Seen–.32.07–4.85<.001
minBF.22.063.62<.001
ABF * Type.00.08.02.981
ABF * Seen.07.061.10.273
Type * Seen.87.117.98<.001
minBF * Type–.16.07–2.35.018
minBF * Seen–.11.05–2.00.045
ABF * Type * Seen–.11.08–1.47.142
minBF * Type * Seen.09.061.49.137
EXPERIMENT 2
β^SEzp
Intercept.06.09.71.473
ABF.08.071.07.285
Type–.10.09–1.15.252
Seen–.26.08–3.05.002
minBF.14.043.46<.001
ABF * Type.02.10.25.800
ABF * Seen–.01.07–.15.877
Type * Seen.71.135.55<.001
minBF * Type–.04.05–.93.355
minBF * Seen–.05.04–1.15.250
ABF * Type * Seen.12.091.31.190
minBF * Type * Seen–.02.05–.52.603
Table 3

Experiments 1–2: Results from the fixed effects structure of the GLMM’s including ABF, minBF, Type (foil vs. word), Seen (unseen vs. seen), and controlling for Block.

EXPERIMENT 1
β^SEzp
Intercept.06.12.47.636
Block–.01.11–.12.906
ABF.07.10.76.448
Type–.24.13–1.86.062
Seen–.33.13–2.44.015
minBF.18.091.96.0498
ABF * Block–.02.10–.20.838
Type * Block.22.131.73.083
ABF * Type.07.15.51.607
Seen * Block.00.13.00.997
ABF * Seen.07.13.52.603
Type * Seen1.05.185.63<.001
minBF * Block.03.10.28.778
minBF * Type–.15.11–1.34.181
minBF * Seen.02.12.14.891
ABF * Type * Block–.06.14–.41.680
ABF * Seen * Block.00.12.02.986
Type * Seen * Block–.19.17–1.07.285
ABF * Type * Seen–.15.18–.79.428
minBF * Type * Block.00.11–.04.967
minBF * Seen * Block–.12.12–1.02.306
minBF * Type * Seen–.01.14–.09.925
ABF * Type * Seen * Block.03.18.19.850
minBF * Type * Seen * Block.10.13.77.443
EXPERIMENT 2
β^SEzp
Intercept–.09.14–.68.494
Block.17.13–1.26.207
ABF–.04.14–.34.736
Type–.06.17–.38.704
Seen–.20.17–1.17.242
minBF.26.073.49<.001
ABF * Block.14.131.03.303
Type * Block–.05.17–.31.754
ABF * Type.19.171.09.274
Seen * Block–.08.15–.55.583
ABF * Seen.11.16.68.497
Type * Seen.75.223.35<.001
minBF * Block–.13.08–1.71.087
minBF * Type–.14.09–1.62.105
minBF * Seen–.19.10–1.92.055
ABF * Type * Block–.16.17–.97.332
ABF * Seen * Block–.13.16–.85.398
Type * Seen * Block–.02.20–.10.922
ABF * Type * Seen–.01.22–.06.949
minBF * Type * Block.12.091.25.211
minBF * Seen * Block.15.091.63.103
minBF * Type * Seen.11.11.99.323
ABF * Type * Seen * Block.15.21.72.468
minBF * Type * Seen * Block–.16.11–1.43.152
DOI: https://doi.org/10.5334/joc.209 | Journal eISSN: 2514-4820
Language: English
Submitted on: Oct 22, 2021
Accepted on: Feb 2, 2022
Published on: Feb 21, 2022
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2022 Jarosław R. Lelonkiewicz, Michael T. Ullman, Davide Crepaldi, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.