Naturvetenskapliga kåserier. Andra samlingen by Bengt Lidforss : Difficulty Assessment for Swedish Learners

How difficult is Naturvetenskapliga kåserier. Andra samlingen for Swedish learners? We have performed multiple tests on its full text (freely available here) of approximately 42,238, crunched all the numbers for you and present the results below.

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Difficulty Assessment Summary

We have estimated Naturvetenskapliga kåserier. Andra samlingen to have a difficulty score of 70. Here're its scores:

Measure Score
easy difficult (1 - 100)
Overall Difficulty 70% 70
Vocabulary Difficulty 80% 80
Grammatical Difficulty 60% 60

Vocabulary Difficulty: Breakdown

80%

Vocabulary difficulty: 80%

This score has been calculated based on frequency vocabulary (the top most frequently used words in Swedish). It combines various measures of Naturvetenskapliga kåserier. Andra samlingen'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 Naturvetenskapliga kåserier. Andra samlingen:

Vocabulary difficulty breakdown for Naturvetenskapliga kåserier. Andra samlingen: a test for Swedish top frequency vocabulary

We have also calculated the following approximate data on the vocabulary in Naturvetenskapliga kåserier. Andra samlingen:

Measure Score
Measure Score
Number of words 42,238
Number of unique words 8,788
Number of recognized words for names/places/other entities 662
Number of very rare non-entity words 2,588
Number of sentences 6,574
Average number of words/sentence 6

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 8,612 words (where all the forms of the word are still counted as unique words) in Swedish to be able to read Naturvetenskapliga kåserier. Andra samlingen without a dictionary and fully understand it.

Grammatical Difficulty: Breakdown

60%

Grammatical difficulty: 60%

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 7
Coleman-Liau Index 11
Type/Token Ratio (TTR) 0.208059
Root type/Token Ratio (RTTR) 0.00000492587
Corrected type/Token Ratio (CTTR) 0.00000246294
MTLD Index 66
HDD Index 67
Yule's I Index 76
Lexical Diversity Index (MTLD + HD-D + Yule's I) 70

The type-token ratio (TTR) of Naturvetenskapliga kåserier. Andra samlingen is 0.208059. 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 8,788, while the number of words is 42,238, so the TTR is 8,788 / 42,238 = 0.208059. 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, 8,788 / (42,238 * 42,238) = 0.00000492587), while in CTTR, it is divided by a square of the number of words, multiplied twice 8,788 / 2 * (42,238 * 42,238) = 0.00000246294). 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 7, making it understandable for 7-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 70 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 60.

Other Information about Naturvetenskapliga kåserier. Andra samlingen by Bengt Lidforss

We provide you a sample of the text below, however, the full text of the Naturvetenskapliga kåserier. Andra samlingen is also available free of charge on our website.

Sample of text:

Det märkligaste exemplet på en organism, vars livshistoria bestämmes av kosmiska inflytanden, utgör dock säkerligen den s. k. palolomasken, som på sista åren ådragit sig stor uppmärksamhet från naturforskarnas sida. På många av Söderhavsöarna, t. ex. Samoa-, Fidschi-, Tonga- och Gilbertöarna, uppträda på tider, som infödingarne mycket väl känna till, oerhörda mängder av havsmaskar, som samlas och förtäras som en stor delikatess. Denna mask, som av infödingarna kallas palolo, spelar för dessa öbor ungefär samma rol som sillen ...

Top most frequently used words in Naturvetenskapliga kåserier. Andra samlingen by Bengt Lidforss*

Position Word Repetitions Part of all words
Position Word Repetitions Part of all words
1 och 1,131 2.68%
2 som 1,062 2.51%
3 att 945 2.24%
4 av 803 1.9%
5 en 773 1.83%
6 den 671 1.59%
7 de 655 1.55%
8 det 606 1.43%
9 460 1.09%
10 är 428 1.01%
11 till 425 1.01%
12 med 402 0.95%
13 för 382 0.9%
14 man 360 0.85%
15 ett 315 0.75%
16 296 0.7%
17 sig 294 0.7%
18 dessa 194 0.46%
19 men 192 0.45%
20 om 183 0.43%
21 hos 181 0.43%
22 har 181 0.43%
23 från 171 0.4%
24 även 163 0.39%
25 genom 162 0.38%
26 icke 145 0.34%
27 äro 141 0.33%
28 denna 136 0.32%
29 detta 135 0.32%
30 kan 134 0.32%
31 eller 131 0.31%
32 utan 131 0.31%
33 vid 127 0.3%
34 andra 120 0.28%
35 sin 118 0.28%
36 under 114 0.27%
37 ej 114 0.27%
38 113 0.27%
39 än 103 0.24%
40 ha 93 0.22%
41 kunna 91 0.22%
42 vi 86 0.2%
43 vilka 81 0.19%
44 samma 81 0.19%
45 vara 81 0.19%
46 gröna 79 0.19%
47 alltså 79 0.19%
48 endast 78 0.18%
49 när 78 0.18%
50 efter 77 0.18%
51 mot 74 0.18%
52 där 74 0.18%
53 mellan 74 0.18%
54 blad 72 0.17%
55 skulle 69 0.16%
56 bladen 67 0.16%
57 alla 66 0.16%
58 ur 65 0.15%
59 sedan 62 0.15%
60 emellertid 62 0.15%
61 växten 62 0.15%
62 däremot 61 0.14%
63 mycket 61 0.14%
64 ex 61 0.14%
65 växterna 60 0.14%
66 nu 60 0.14%
67 var 59 0.14%
68 växter 59 0.14%
69 redan 59 0.14%
70 vatten 58 0.14%
71 dem 58 0.14%
72 också 56 0.13%
73 dock 56 0.13%
74 fall 56 0.13%
75 röda 54 0.13%
76 sådana 53 0.13%
77 fullkomligt 52 0.12%
78 här 52 0.12%
79 del 51 0.12%
80 båda 51 0.12%
81 sina 51 0.12%
82 två 50 0.12%
83 sätt 50 0.12%
84 medan 49 0.12%
85 ju 49 0.12%
86 allt 49 0.12%
87 år 48 0.11%
88 in 45 0.11%
89 ut 45 0.11%
90 olika 45 0.11%
91 vad 45 0.11%
92 dess 43 0.1%
93 levande 43 0.1%
94 bli 43 0.1%
95 form 43 0.1%
96 ljuset 42 0.1%
97 ljus 42 0.1%
98 över 41 0.1%
99 blott 41 0.1%
100 deras 41 0.1%
101 upp 40 0.09%
102 större 40 0.09%
103 någon 40 0.09%
104 många 39 0.09%
105 senare 39 0.09%
106 nya 39 0.09%
107 tid 38 0.09%
108 gäller 38 0.09%
109 kraft 37 0.09%
110 högra 37 0.09%
111 ofta 37 0.09%
112 äga 37 0.09%
113 hela 36 0.09%
114 nämligen 36 0.09%
115 särskilt 36 0.09%
116 blir 36 0.09%
117 inre 36 0.09%
118 själva 36 0.09%
119 kommer 36 0.09%
120 lika 36 0.09%
121 djur 35 0.08%
122 yttre 35 0.08%
123 proc 35 0.08%
124 stor 35 0.08%
125 blommor 35 0.08%
126 fallet 34 0.08%
127 alldeles 34 0.08%
128 fram 33 0.08%
129 sitt 33 0.08%
130 första 33 0.08%
131 sådan 32 0.08%
132 våra 31 0.07%
133 kunde 31 0.07%
134 han 31 0.07%
135 helt 31 0.07%
136 Vries 31 0.07%
137 vilken 31 0.07%
138 flera 30 0.07%
139 något 30 0.07%
140 annan 30 0.07%
141 vanliga 30 0.07%
142 ena 30 0.07%
143 mängd 30 0.07%
144 mörker 30 0.07%
145 nog 30 0.07%
146 ännu 29 0.07%
147 grad 29 0.07%
148 liksom 29 0.07%
149 vars 29 0.07%
150 varje 29 0.07%
151 undersökningar 29 0.07%
152 finns 29 0.07%
153 först 29 0.07%
154 egenskaper 29 0.07%
155 några 29 0.07%
156 gång 28 0.07%
157 socker 28 0.07%
158 numera 28 0.07%
159 omkring 28 0.07%
160 vissa 28 0.07%
161 åter 27 0.06%
162 mindre 27 0.06%
163 framkalla 27 0.06%
164 synes 27 0.06%
165 växtens 27 0.06%
166 längre 26 0.06%
167 anlag 26 0.06%
168 göra 26 0.06%
169 omständigheter 26 0.06%
170 stärkelse 26 0.06%
171 vilkas 26 0.06%
172 gula 26 0.06%
173 grund 25 0.06%
174 oss 25 0.06%
175 visa 25 0.06%
176 vita 25 0.06%
177 normala 25 0.06%
178 varit 25 0.06%
179 viss 25 0.06%
180 finner 25 0.06%

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 Naturvetenskapliga kåserier. Andra samlingen by Bengt Lidforss

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.