This study takes Kango antei as an example, elucidates how the semantic function is affected by the use of five adnominal modification: na, no, shita, tekiφ, and tekina. Specifically, we focus on three aspects: (1) frequency and range, (2) feature genres, and (3) collocations. The results show that: (1) The frequency of antei-shita is the highest and the range of its use is the widest among the five patterns, (2) antei-na is characteristically used in the textbook genre, while antei-teki (na) is used in the white paper and law genres, (3) The use of antei as a technical term is limited to the form of antei-na, and other forms are used for general meaning. We conclude that there are manifold semantics and usages of the word antei, depending on the followed adnominal modification.

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The purpose of this study is to support foreigners living in Japan to get a job as "an independent language user" from the viewpoint of Japanese language education. Therefore, I investigated the characteristics of the vocabulary required to read job information and the characteristics of the vocabulary required to write a resume. As survey data, I used text data form "HelloWork internet service" and text data form sentences of resume written by native Japanese speakers, and analyzed it for the part-speech composition, frequency of appearance, and degree of characteristics. As a result, it was clarified that nouns were remarkably large as part of speech and words in the upper intermediate level were the most common in the job information, and that the tendency did not differ between industries. Regarding the sentences of resume, it became clear that there are characteristic words such as kisha, shibou, and tazusawaru. In addition, it became clear that there are frequent sentence patterns such as tai-to-kangaeru.

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Linguistic data are typically classified based on the nature of the values into one of four categories known as the nominal scales, ordinal scales, interval scales, and ratio scales. The nominal scales and ordinal scales are useful for qualitative data and the interval scales and ratio scales are useful for quantitative data. Since each of these statistical scales allows different calculations, there are different statistical and data visualization methods suitable to each scale. This paper gives an overview of these methods. In addition, given that the majority of linguistic data are qualitative, in this paper, we show that researchers must be careful when taking a statistical approach to such data.

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