Diablo Cojuelo by Luis Vélez de Guevara : Difficulty Assessment for Spanish Learners

How difficult is Diablo Cojuelo for Spanish learners? We have performed multiple tests on its full text of approximately 82,958, crunched all the numbers for you and present the results below.

Difficulty Assessment Summary

We have estimated Diablo Cojuelo to have a difficulty score of 70. Here're its scores:

Measure Score
easy difficult (1 - 100)
Overall Difficulty 70% 70
Vocabulary Difficulty 100% 100
Grammatical Difficulty 40% 40

Vocabulary Difficulty: Breakdown

100%

Vocabulary difficulty: 100%

This score has been calculated based on frequency vocabulary (the top most frequently used words in Spanish). It combines various measures of Diablo Cojuelo's text analyzed in terms of frequency vocabulary: a plain vocabulary score, frequency-weighted vocabulary score, banded frequency vocabulary scores based on vocabulary of the text falling in the top 1,000 or 2,000 most frequent words, etc. Here's a further breakdown of how often the top most frequently used words in Spanish appear in the full text of Diablo Cojuelo:

Vocabulary difficulty breakdown for Diablo Cojuelo: a test for Spanish top frequency vocabulary

We have also calculated the following approximate data on the vocabulary in Diablo Cojuelo:

Measure Score
Measure Score
Number of words 82,958
Number of unique words 16,026
Number of recognized words for names/places/other entities 4,601
Number of very rare non-entity words 6,202
Number of sentences 9,775
Average number of words/sentence 8

There is some research suggesting that that you need to know about 98% of a text's vocabulary in order to be able to infer the meaning of unknown words when reading. If true, this means that you would need to know around 15,705 words (where all the forms of the word are still counted as unique words) in Spanish to be able to read Diablo Cojuelo without a dictionary and fully understand it.

Grammatical Difficulty: Breakdown

40%

Grammatical difficulty: 40%

Here is the further grammatical comparison on this text. You can find an explanation of all these scores below.

Measure Score
Measure Score
Automated Readability Index 5
Coleman-Liau Index 8
Type/Token Ratio (TTR) 0.193182
Root type/Token Ratio (RTTR) 0.00000232867
Corrected type/Token Ratio (CTTR) 0.00000116434
MTLD Index 47
HDD Index 48
Yule's I Index 43
Lexical Diversity Index (MTLD + HD-D + Yule's I) 46

The type-token ratio (TTR) of Diablo Cojuelo is 0.193182. The TTR is the most basic measure of lexical diversity. To calculate it, we divide the number of unique words by the number of words in the text. For example, for this text, the number of unique words is 16,026, while the number of words is 82,958, so the TTR is 16,026 / 82,958 = 0.193182. However, the TTR is a very crude measure, as it is extremely dependent on text length. The longer the text, the lower the TTR is usually going to be, since common words tend to often repeat. Especially since the number of words in this text is more than 1,000, the TTR is not likely to give an accurate measure.

The root type-token ratio (RTTR) and corrected type-token ratio (CTTR) are measures which were suggested by researchers to partially address the problem of TTR's variance on text length. In the RTTR, the number of unique words is divided by a square of the number of words (therefore, 16,026 / (82,958 * 82,958) = 0.00000232867), while in CTTR, it is divided by a square of the number of words, multiplied twice 16,026 / 2 * (82,958 * 82,958) = 0.00000116434). However, these measures are not as easily readable, and also there is a growing body of research asserting that CTTR and RTTR do not effectively address the problems of text length. Therefore, while we do provide the full text's TTR, RTTR and CTTR on this page, these fiqures do not form part of our final calculations.

The Automated Readability Index (ARI) is one readability measure that has been developed by researchers over the years. The formula for calculating the ARI is as follows:
Formula for calculating the Automated Readability Index

The ARI should compute a reading level approximately corresponding to the reader's grade level (assuming the reader undertakes formal education). Thus, for example, a value of 1 is kindergarten level, while a value of 12 or 13 is the last year of school, and 14 is a sophomore at college. The current ARI of this text is 5, making it understandable for 5-grade students at their expected level of education.

The Coleman Liau Index (CLI) is a similar index designed by Meri Coleman and T. L. Liau, and it is supposed to compute the grade level of the reader (thus, for example, sophomore level material would be around grade 14, or year 14 of formal education, while kindergarten / primary school level material would be close to grade 1 in the CLI). The CLI is usually slightly higher than the ARI. The CLI is computed with this formula:
Formula for calculating the Coleman-Liau Readability Index

It is notable that other indexes exist, such as the Flesch-Kincaid Reading Ease, Gunning-Fog Score, and others, but we have chosen not to include them, since, contrary to the ARI and CLI, such other indexes are based on a syllable count and therefore arguably only work for English and not Spanish.

We compute a further compound lexical diversity index, which should range from 1 to a 100 (with the standard deviation being around 10, and its average value being around 50) - it is 46 in the present case. The compound lexical diversity index consists of the following indexes, averaged out (and also provided in the table above):

  • the Measure of Textual Lexical Diversity (MTLD) index - a measure which is based on computing the TTR for increasingly larger parts of the text until the TTR drops below a certain threshold point (around 0.7 in our case) - in which case, the TTR is reset, and the overall counter is increased; the counter is at the end divided by the number of words in text; as a result, the MTLD does not significantly vary by text length;
  • the Yule's I index (based on Yule's K characteristic inverted) - an index based on the work of the statistician G.U. Yule, who published his index of Frequency Vocabulary in his paper "The statistical study of literary vocabulary"; Yule's I takes into account the number of words in the text, and a compound summed measure of word frequency;
  • the Hypergeometric Distribution D (HD-D) index (based on vocd) - an index which assesses the contribution of each word to the diversity of the text; to calculate such contributions, a hypergeometric distribution is used to compute probabilities of each word appearing in word samples extracted from the text; then such distributions are divided by sample sizes and added up;

Our overall measure of grammatical diversity is based on a combination of the compound lexical diversity index (which includes the MTLD, Yule's I and HD-D indexes), the ARI and CLI, all normalized and given certain weight. The score should normally range from 1 to 100. In this case, the score is 40.

Other Information about Diablo Cojuelo by Luis Vélez de Guevara

We provide you a sample of the text below, however, the full text of the Diablo Cojuelo is also available free of charge on our website.

Sample of text:

..." Teniase al Diablo Cojuelo, como dice el refran, por el mas listo de todos: Esperanza Bonfilla, procesada por la Inquisicion de Valencia en 1600, hizo que cierta mujer, para atraer a un hombre, "hiciese vn conjuro en la forma siguiente: tomando vna escoba, la puso vna toca como muger, y encendida vna bela que no fuese bendita, se arrodillo delante de la escoba, y sin hacer cruz, juntas las manos, dixo: Marta, Martica, no la santa ni la digna, ni la digna de rogar, ni la que esta en el altar, sino la que de noche andas por las beredas y los dias por las encrebelladas, yo te conjuro con Satanas y con Barrabas, con Bercebu y todos los diablos, y con el diablo coxo, que corre mas que todos, que todos vais a fulano y le deis tiempo para vestirse y le traigais por puntos ante mi y mis ojos, ...

Top most frequently used words in Diablo Cojuelo by Luis Vélez de Guevara*

Position Word Repetitions Part of all words
Position Word Repetitions Part of all words
1 de 5,462 6.58%
2 que 2,918 3.52%
3 la 2,388 2.88%
4 en 2,191 2.64%
5 el 2,083 2.51%
6 los 1,100 1.33%
7 se 917 1.11%
8 por 890 1.07%
9 del 821 0.99%
10 las 791 0.95%
11 con 758 0.91%
12 Nota 647 0.78%
13 su 605 0.73%
14 no 594 0.72%
15 es 515 0.62%
16 como 510 0.61%
17 un 478 0.58%
18 lo 449 0.54%
19 al 419 0.51%
20 una 385 0.46%
21 mas 342 0.41%
22 para 331 0.4%
23 don 312 0.38%
24 esta 303 0.37%
25 le 294 0.35%
26 sus 238 0.29%
27 dijo 222 0.27%
28 si 201 0.24%
29 porque 196 0.24%
30 me 177 0.21%
31 dos 175 0.21%
32 este 169 0.2%
33 ha 154 0.19%
34 sin 151 0.18%
35 Velez 150 0.18%
36 Cleofas 147 0.18%
37 Cojuelo 146 0.18%
38 era 146 0.18%
39 habia 145 0.17%
40 tan 144 0.17%
41 muy 143 0.17%
42 senor 140 0.17%
43 dice 140 0.17%
44 mi 137 0.17%
45 ni 133 0.16%
46 Sevilla 127 0.15%
47 donde 120 0.14%
48 aquel 115 0.14%
49 todo 114 0.14%
50 ser 112 0.14%
51 son 110 0.13%
52 sobre 109 0.13%
53 todos 104 0.13%
54 quien 104 0.13%
55 _El 104 0.13%
56 yo 102 0.12%
57 decir 99 0.12%
58 otro 99 0.12%
59 Madrid 97 0.12%
60 bien 96 0.12%
61 pues 95 0.11%
62 tal 94 0.11%
63 tiene 93 0.11%
64 II 92 0.11%
65 entre 92 0.11%
66 edicion 92 0.11%
67 otros 91 0.11%
68 hay 89 0.11%
69 Bonilla 87 0.1%
70 cuando 87 0.1%
71 fue 85 0.1%
72 aun 85 0.1%
73 despues 83 0.1%
74 pero 83 0.1%
75 mismo 83 0.1%
76 esto 80 0.1%
77 gran 79 0.1%
78 han 76 0.09%
79 asi 75 0.09%
80 uno 75 0.09%
81 ella 75 0.09%
82 nombre 75 0.09%
83 ya 74 0.09%
84 hasta 74 0.09%
85 cual 74 0.09%
86 _de 73 0.09%
87 poco 73 0.09%
88 casa 72 0.09%
89 aquella 72 0.09%
90 tiempo 72 0.09%
91 calle 71 0.09%
92 mano 71 0.09%
93 unos 70 0.08%
94 parte 70 0.08%
95 estas 70 0.08%
96 menos 70 0.08%
97 hacer 69 0.08%
98 otra 68 0.08%
99 Dios 65 0.08%
100 pag 65 0.08%
101 aqui 64 0.08%
102 les 64 0.08%
103 ellos 63 0.08%
104 cosa 63 0.08%
105 dicho 62 0.07%
106 otras 61 0.07%
107 sino 61 0.07%
108 he 61 0.07%
109 ciudad 60 0.07%
110 Guevara 60 0.07%
111 mundo 60 0.07%
112 Lope 60 0.07%
113 siempre 59 0.07%
114 antes 59 0.07%
115 noche 59 0.07%
116 habian 59 0.07%
117 acto 58 0.07%
118 Juan 57 0.07%
119 hoy 57 0.07%
120 Quevedo 56 0.07%
121 San 56 0.07%
122 te 56 0.07%
123 Perez 56 0.07%
124 dia 55 0.07%
125 tanto 55 0.07%
126 lugar 55 0.07%
127 anos 55 0.07%
128 desde 54 0.07%
129 ver 54 0.07%
130 vn 53 0.06%
131 Academia 53 0.06%
132 libro 53 0.06%
133 estos 53 0.06%
134 algunos 53 0.06%
135 _Diccionario_ 52 0.06%
136 aunque 52 0.06%
137 medio 52 0.06%
138 manos 52 0.06%
139 _La 51 0.06%
140 tu 51 0.06%
141 viene 50 0.06%
142 tambien 50 0.06%
143 cosas 50 0.06%
144 Conde 50 0.06%
145 Diablo 49 0.06%
146 fol 49 0.06%
147 cuatro 48 0.06%
148 Rey 47 0.06%
149 Espana 47 0.06%
150 diciendo 47 0.06%
151 demas 46 0.06%
152 tres 46 0.06%
153 estaba 46 0.06%
154 nos 45 0.05%
155 mayor 44 0.05%
156 principe 44 0.05%
157 alli 43 0.05%
158 Gonzalez 43 0.05%
159 autor 43 0.05%
160 solo 43 0.05%
161 Marques 43 0.05%
162 respondio 42 0.05%
163 grande 42 0.05%
164 muchos 41 0.05%
165 dona 41 0.05%
166 mucho 41 0.05%
167 todas 41 0.05%
168 decia 41 0.05%
169 ano 40 0.05%
170 III 40 0.05%
171 tenia 40 0.05%
172 versos 40 0.05%
173 estan 40 0.05%
174 Luis 40 0.05%
175 parece 39 0.05%
176 Vega 39 0.05%
177 fuera 39 0.05%
178 hizo 39 0.05%
179 da 39 0.05%
180 tomo 39 0.05%
181 _Quijote_ 39 0.05%
182 unas 39 0.05%

This list excludes punctuation or single-letter words, also some different-case repeats of the same words.

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