Falluckan. Anekdoter och Karaktersdrag samlade av Teater-Nisse by Carl Henrik Atterling : Difficulty Assessment for Swedish Learners

How difficult is Falluckan. Anekdoter och Karaktersdrag samlade av Teater-Nisse for Swedish learners? We have performed multiple tests on its full text (freely available here) of approximately 13,560, crunched all the numbers for you and present the results below.

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Difficulty Assessment Summary

We have estimated Falluckan. Anekdoter och Karaktersdrag samlade av Teater-Nisse to have a difficulty score of 73. Here're its scores:

Measure Score
easy difficult (1 - 100)
Overall Difficulty 73% 73
Vocabulary Difficulty 94% 94
Grammatical Difficulty 53% 53

Vocabulary Difficulty: Breakdown

94%

Vocabulary difficulty: 94%

This score has been calculated based on frequency vocabulary (the top most frequently used words in Swedish). It combines various measures of Falluckan. Anekdoter och Karaktersdrag samlade av Teater-Nisse'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 Swedish appear in the full text of Falluckan. Anekdoter och Karaktersdrag samlade av Teater-Nisse:

Vocabulary difficulty breakdown for Falluckan. Anekdoter och Karaktersdrag samlade av Teater-Nisse: a test for Swedish top frequency vocabulary

We have also calculated the following approximate data on the vocabulary in Falluckan. Anekdoter och Karaktersdrag samlade av Teater-Nisse:

Measure Score
Measure Score
Number of words 13,560
Number of unique words 3,839
Number of recognized words for names/places/other entities 842
Number of very rare non-entity words 1,050
Number of sentences 2,492
Average number of words/sentence 5

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 3,762 words (where all the forms of the word are still counted as unique words) in Swedish to be able to read Falluckan. Anekdoter och Karaktersdrag samlade av Teater-Nisse without a dictionary and fully understand it.

Grammatical Difficulty: Breakdown

53%

Grammatical difficulty: 53%

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 4
Coleman-Liau Index 7
Type/Token Ratio (TTR) 0.283112
Root type/Token Ratio (RTTR) 0.0000208785
Corrected type/Token Ratio (CTTR) 0.0000104392
MTLD Index 57
HDD Index 69
Yule's I Index 85
Lexical Diversity Index (MTLD + HD-D + Yule's I) 71

The type-token ratio (TTR) of Falluckan. Anekdoter och Karaktersdrag samlade av Teater-Nisse is 0.283112. 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 3,839, while the number of words is 13,560, so the TTR is 3,839 / 13,560 = 0.283112. 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, 3,839 / (13,560 * 13,560) = 0.0000208785), while in CTTR, it is divided by a square of the number of words, multiplied twice 3,839 / 2 * (13,560 * 13,560) = 0.0000104392). 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 4, making it understandable for 4-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 Swedish.

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 71 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 53.

Other Information about Falluckan. Anekdoter och Karaktersdrag samlade av Teater-Nisse by Carl Henrik Atterling

We provide you a sample of the text below, however, the full text of the Falluckan. Anekdoter och Karaktersdrag samlade av Teater-Nisse is also available free of charge on our website.

Sample of text:

ex. dagsljus med x, och vaxljus med gs, inntyg o. s. v., allt franska ord. Pjesen är fransk och — icke lokaliserad; spelas alltså i Frankrike, personen är alltså fransman .... och man fick en ny anledning att beundra »snillet och smaken» hos teaterns »litterära biträde», hr W—r, hvilken lärer öfversatt pjesen. * En viss person hade i vintras det missödet att falla ned genom en fallucka på Dramatiska teatern och erhöll dervid, enligt officiela tidningen, »svårare skador». — »Nå, men hvad i all verlden har också herr W—r vid Dramatiska teatern att göra!» utropade en af våra skämtare, vid underrättelsen om fallet. * Hr Georg Dahlqvist har, som man vet, spelat många maktpåliggande roler, men aldrig har Teater-Nisse förr än helt nyligen fått veta, att han spelat ej allenast Posa, Romeo, Erik XIV, Engelbrekt, Hakon ...

Top most frequently used words in Falluckan. Anekdoter och Karaktersdrag samlade av Teater-Nisse by Carl Henrik Atterling*

Position Word Repetitions Part of all words
Position Word Repetitions Part of all words
1 och 330 2.43%
2 att 244 1.8%
3 en 207 1.53%
4 det 201 1.48%
5 för 176 1.3%
6 af 167 1.23%
7 161 1.19%
8 som 147 1.08%
9 den 145 1.07%
10 är 142 1.05%
11 jag 113 0.83%
12 med 112 0.83%
13 de 97 0.72%
14 till 91 0.67%
15 han 90 0.66%
16 sig 87 0.64%
17 Hofmarskalken 67 0.49%
18 ett 65 0.48%
19 teatern 64 0.47%
20 hr 64 0.47%
21 har 63 0.46%
22 62 0.46%
23 inte 60 0.44%
24 der 59 0.44%
25 om 59 0.44%
26 man 50 0.37%
27 Men 49 0.36%
28 46 0.34%
29 icke 45 0.33%
30 skall 45 0.33%
31 var 43 0.32%
32 vid 38 0.28%
33 Nisse 38 0.28%
34 mig 36 0.27%
35 kan 36 0.27%
36 Teater 35 0.26%
37 sin 34 0.25%
38 Spelas 34 0.25%
39 väl 33 0.24%
40 du 32 0.24%
41 Kontrollören 30 0.22%
42 Kongl 30 0.22%
43 hvad 30 0.22%
44 herr 30 0.22%
45 skulle 30 0.22%
46 Ja 28 0.21%
47 nu 28 0.21%
48 efter 27 0.2%
49 här 27 0.2%
50 eller 25 0.18%
51 Kapellmästaren 25 0.18%
52 ej 25 0.18%
53 min 24 0.18%
54 ha 24 0.18%
55 24 0.18%
56 honom 24 0.18%
57 genom 23 0.17%
58 hade 23 0.17%
59 under 23 0.17%
60 än 22 0.16%
61 gör 22 0.16%
62 vara 21 0.15%
63 vet 21 0.15%
64 öfver 20 0.15%
65 se 20 0.15%
66 andra 20 0.15%
67 får 20 0.15%
68 20 0.15%
69 akter 19 0.14%
70 komedi 19 0.14%
71 alla 19 0.14%
72 vill 19 0.14%
73 akt 19 0.14%
74 hela 18 0.13%
75 hvilken 18 0.13%
76 måste 18 0.13%
77 denna 18 0.13%
78 något 18 0.13%
79 Pettersson 18 0.13%
80 någon 17 0.13%
81 upp 17 0.13%
82 första 17 0.13%
83 går 17 0.13%
84 ska 17 0.13%
85 göra 17 0.13%
86 dem 16 0.12%
87 th 16 0.12%
88 såsom 16 0.12%
89 också 16 0.12%
90 hvilka 16 0.12%
91 Inspektören 16 0.12%
92 vi 16 0.12%
93 hofmarskalk 16 0.12%
94 hafva 15 0.11%
95 herrn 15 0.11%
96 vår 15 0.11%
97 nog 15 0.11%
98 äfven 15 0.11%
99 detta 15 0.11%
100 röst 14 0.1%
101 ju 14 0.1%
102 ut 14 0.1%
103 dag 14 0.1%
104 scen 14 0.1%
105 äro 14 0.1%
106 några 14 0.1%
107 sina 14 0.1%
108 förste 14 0.1%
109 sedan 14 0.1%
110 sitt 13 0.1%
111 Hvarför 13 0.1%
112 operan 13 0.1%
113 hrr 13 0.1%
114 hans 13 0.1%
115 blir 13 0.1%
116 gång 13 0.1%
117 teaterns 13 0.1%
118 utan 13 0.1%
119 annan 13 0.1%
120 bli 12 0.09%
121 ur 12 0.09%
122 aldrig 12 0.09%
123 ta 12 0.09%
124 direktören 12 0.09%
125 hon 12 0.09%
126 blef 12 0.09%
127 Grabow 11 0.08%
128 Hermansson 11 0.08%
129 allt 11 0.08%
130 samt 11 0.08%
131 scenen 11 0.08%
132 många 11 0.08%
133 Dramatiska 11 0.08%
134 åt 11 0.08%
135 11 0.08%
136 hos 11 0.08%
137 dig 11 0.08%
138 tid 10 0.07%
139 Nilsson 10 0.07%
140 ty 10 0.07%
141 oss 10 0.07%
142 säga 10 0.07%
143 ingen 10 0.07%
144 stod 10 0.07%
145 Wij 10 0.07%
146 alldeles 10 0.07%
147 samma 10 0.07%
148 från 10 0.07%
149 fram 9 0.07%
150 Frun 9 0.07%
151 sådan 9 0.07%
152 bra 9 0.07%
153 ställningssteg 9 0.07%
154 gjort 9 0.07%
155 in 9 0.07%
156 Maskinmästaren 9 0.07%
157 fru 9 0.07%
158 inom 9 0.07%

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

If you think the text would be accessible to you, you can read it on our site (click on the cover to access):

Cover of Falluckan. Anekdoter och Karaktersdrag samlade av Teater-Nisse by Carl Henrik Atterling

Other resources and languages

If you like this analysis, you should have a look at out our lists of Swedish short stories and Swedish books.

If you like literature as a means to learn languages - please take a look at our project Interlinear Books. We even have a Swedish Interlinear book available for purchase.