This study intends to select useful vocabularies in practical business for foreign student with purpose of employment of domestic companies. To do that, this study built a corpus with the articles of economic, industrial, securities and real estate se... This study intends to select useful vocabularies in practical business for foreign student with purpose of employment of domestic companies. To do that, this study built a corpus with the articles of economic, industrial, securities and real estate sections of ‘Korea Economic Daily’ during 1 year from 1st, September of 2014 to 31st, August of 2015. With this raw corpus built, word phrase analysis based statistic approach was proceeded using UNIX commanding language. As a results, the total number of word phrases was 3,908,598 and the types of word phrases were 463,636. In most preceding studies, regarding word selection for academic purpose of foreign students majoring in economics and business administration, the sizes of corpus were usually less than a million of word phrases but in this study, the size of corpus was 3.9millions of word phrases. In terms of the representativeness of corpus, this study is distinguished from those preceding studies with the formation of the base for meaningful word selection as far as corpus size is concerned. In this study, there are 3 directions proceeded for selecting vocabularies. Firstly, through morpheme analysis by intellectual morpheme analyzer, 54,352 of noun vocabularies were extracted from classified word class. And there were 9,013 of vocabularies as 95% of coverage and, as a result of removing fundamental vocabularies, there were 6,715 of vocabularies. Subsequently removing the academic vocabularies, there were 6,323 of vocabularies remained and finally there were 1,365 of economy related technical terms with more than 100 frequencies. Secondly, compound word was selected by analyzing in word phrase unit. From 465,635 types of word phrases, 27,000 types of phrases with 75% of accumulated frequency (coverage) were analyzed and 1,119 of vocabularies focusing on compound word were selected. In succession, through ‘expert searching window’ of ‘KkamJjackSae’ (the name of the corpus program) the occurrence frequencies of 1,119 vocabularies were figured out. Lastly, based on the result of morpheme analysis, prefix and suffix with frequent occurrence were extracted and following that, total 890 of affix derivative words with these affixes above including 705 of suffix derivative words and 185 of prefix derivative words were selected through ‘expert searching window’ of ‘KkamJjackSae’. On the next process, total 1,832 of vocabularies were finally selected following 2 vocabulary ratings. Those are 717 of words from morpheme analysis selection and, 714 of vocabularies from word phrase analysis selection and 401 of vocabularies from affix analysis selection. These selected vocabularies were subdivided into A, B and C classes depending on its importance in each field of finance, industry, economy, real estate and common field and made for lexicon list accordingly. Different from preceding studies mainly dealing with noun centered word selection, this study suggested the relationship of combining predicative nouns and function verbs through word formation unit analysis and word extension stage through compound and affix derivative word formation. Firstly, through comparing noun roots of ‘hada’ and ‘doida’ which were selected by frequent occurring ending analysis resulted from morpheme analysis, with the vocabularies selected by morpheme analysis, 105 overlapping vocabularies were selected. By learning 105 of overlapping noun roots, they extend into predicates combined with ‘hada’ and ‘doida’ and consequently extend into sentence formation. Consequently, these vocabularies are very useful for developing proper syllabus of vocabulary instruction curriculum. Secondly, based on learning of 269 overlapping words between morpheme analysis selected words and phrases analysis selected words as well as affix analysis selected words, this is regarded as an efficient vocabulary learning with extending vocabularies from simple word into compound and affix derivatives. In the case of planning and designing vocabulary learning course related to business, this 269 of vocabularies and the lexicon list selected by this word phrase analysis and affix analysis can be useful in developing the vocabulary learning syllabus. Those of 46 overlapping vocabularies by comparison with the lexicon list of the 4 preceding studies (regarding word selection for academic purpose of foreign students majoring in economics and business administration) and lexicon list of this study, are very important vocabularies academically as well as practically. And 391 vocabularies of this study occurring more than once from the preceding studies’ lexicon lists, are regarded as the vocabulary to be acquired subsequently. In the case of planning business practice related vocabulary instruction curriculum, therefore, 46 of vocabulary list and 391 of the list can be used as a reference for vocabulary instruction syllabus with sequential learning stage. The vocabularies classified in economy, finance, industry, real estate and common field are expected to be used as related words for each business area. Moreover, common field vocabularies, the words of closely connected and related to each field, should be learned first. Vocabularies of common field are usually the vocabularies with high importance to be learned prior to each category’s vocabularies. The vocabularies based on the importance level can be proceeded for vocabulary learning depending on its level of importance in each stage. These categorized classification and importance level classification have complementary effect and make better word availability for learning. In this study, 1 year of economic news articles were used as data for a corpus. But as time passes on, there will be new vocabularies representing new economic environment. Accordingly, vocabularies of previous news articles will be less important comparatively. 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