Search results
Results From The WOW.Com Content Network
Word count is commonly used by translators to determine the price of a translation job. Word counts may also be used to calculate measures of readability and to measure typing and reading speeds (usually in words per minute). When converting character counts to words, a measure of 5 or 6 characters to a word is generally used for English. [1]
The result is a keyword density value. When calculating keyword density, ignore html tags and other embedded tags which will not appear in the text of the page once published. When calculating the density of a keyword phrase, the formula would be (/), [1] where Nwp is the number of words in the phrase. So, for example, for a four-hundred word ...
The Coleman–Liau index is calculated with the following formula: = L is the average number of letters per 100 words and S is the average number of sentences per 100 words. Note that the multiplication operator is often omitted (as is common practice in mathematical formulas when it is clear that multiplication is implied).
In particular, the frequencies of the closed class of function words in English is better described with s lower than 1, while open-ended vocabulary growth with document size and corpus size require s greater than 1 for convergence of the Generalized Harmonic Series. [3] Well's War of the Worlds in plain text, in a book code, and in a Vigenère ...
However, these formulas are not a hard rule and the resulting number of classes determined by formula may not always be exactly suitable with the data being dealt with. Calculate the range of the data (Range = Max – Min) by finding the minimum and maximum data values. Range will be used to determine the class interval or class width.
To prevent a zero probability being assigned to unseen words, each word's probability is slightly lower than its frequency count in a corpus. To calculate it, various methods were used, from simple "add-one" smoothing (assign a count of 1 to unseen n-grams, as an uninformative prior) to more sophisticated models, such as Good–Turing ...
The lexical density is the proportion of content words (lexical items) in a given discourse. It can be measured either as the ratio of lexical items to total number of words, or as the ratio of lexical items to the number of higher structural items in the sentences (for example, clauses).
The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]