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  2. Letter frequency - Wikipedia

    en.wikipedia.org/wiki/Letter_frequency

    The California Job Case was a compartmentalized box for printing in the 19th century, sizes corresponding to the commonality of letters. The frequency of letters in text has been studied for use in cryptanalysis, and frequency analysis in particular, dating back to the Arab mathematician al-Kindi (c. AD 801–873 ), who formally developed the method (the ciphers breakable by this technique go ...

  3. Frequency analysis - Wikipedia

    en.wikipedia.org/wiki/Frequency_analysis

    A typical distribution of letters in English language text. Weak ciphers do not sufficiently mask the distribution, and this might be exploited by a cryptanalyst to read the message. In cryptanalysis, frequency analysis (also known as counting letters) is the study of the frequency of letters or groups of letters in a ciphertext.

  4. Most common words in English - Wikipedia

    en.wikipedia.org/wiki/Most_common_words_in_English

    The OEC includes a wide variety of writing samples, such as literary works, novels, academic journals, newspapers, magazines, Hansard's Parliamentary Debates, blogs, chat logs, and emails. [2] Another English corpus that has been used to study word frequency is the Brown Corpus, which was compiled by researchers at Brown University in the 1960s ...

  5. Personal Shorthand - Wikipedia

    en.wikipedia.org/wiki/Personal_Shorthand

    High-frequency letter groupings within words ("g" for "-ing", "s" for "-tion", etc.), known as Phonetic Abbreviations, are also written with a single letter. In most Personal Shorthand textbooks, the entire Theory is presented in just ten lessons, after which review and practice can lead to writing speeds of 60 to 100 words per minute.

  6. Zipf's law - Wikipedia

    en.wikipedia.org/wiki/Zipf's_law

    Even in English, the deviations from the ideal Zipf's law become more apparent as one examines large collections of texts. Analysis of a corpus of 30,000 English texts showed that only about 15% of the texts in it have a good fit to Zipf's law. Slight changes in the definition of Zipf's law can increase this percentage up to close to 50%. [45]

  7. Trigram - Wikipedia

    en.wikipedia.org/wiki/Trigram

    Frequency [ edit ] Context is very important, varying analysis rankings and percentages are easily derived by drawing from different sample sizes, different authors; or different document types: poetry, science-fiction, technology documentation; and writing levels: stories for children versus adults, military orders, and recipes.