Inter-textual Vocabulary Growth Patterns for Marine Engineering English. FENG Zhi-wei Institute of Applied Linguistics, The Ministry of Education, Beijing, China Communication University of China E-mail: [email protected] ABSTRACT.
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2. Existing Vocabulary Growth Models human language
3. DMMEE and Methodology human language
To achieve representativeness and balance in text sample selection, Summers (1991) outlined a number of possible approaches including:
With the aid of software SPSS and data-managing system FoxPro, we explore the five issues of MEE vocabulary growth, including:
Specifically, the task of data processing was conducted via the following steps:
The number of samples in each set is determined by two factors (Fan 2006):
-- Nation (1990) and Nagy (1997) place the vocabulary size of educated native speakers at 20,000;
-- Radford et al. (1999) gives it a higher figure, around 30,000.
4 Vocabulary Growth Models for MEE human language
4. 1 Test of the Existing Vocabulary Growth Models human language
4. 2 A New Vocabulary Growth Model for MEE (tiny circles) for the Sample Set, as well as the corresponding expectations (solid line) using Brunet’s model, Guiraud’s model, Tuldava’s model and Herdan’s model.
and a normally distributed random deviation ε; so itself has a normal distribution, with the expected value E(V(N)i) from fitting the new model being the theoretical mean. These properties are illustrated in above Figure.
Ｗ ＝ Φ（Ｔ）
that is, [3989, 4748].
7 Texts． Conclusion