Prospects for soft statistical computing: describing data and inferring from data with words in the Human Sciences
The main aspects of soft statistics in the Human Sciences will be considered. Our aim will be that soft systems should mimic human linguistic reasoning, and we will apply the methods of granular computing and computing with words to achieve this aim. First, the methodological background will be described, and in this context we will show that the soft computing (SC) approach provides an intelligible philosophical basis for the Human Sciences. By virtue of SC, we may examine hard data in a linguistic form, and this procedure is a user-friendly approach for researchers and students in a manmachine milieu. In practice, we will focus on suggesting new ideas which could be used with soft statistics. Second, on a more concrete level, the following aspects will be considered: (i) SC reasoning algorithms will be presented, and these algorithms will be used in applications; (ii) we will examine soft descriptive statistics which includes soft measurement and soft data compression; (iii) in the context of inferential soft statistics, we will consider soft random distributions, soft statistical hypotheses and tests, and certain advanced soft statistical methods. We will assess our systems using two main criteria, first, we should be able to construct the systems fluently, and second, these systems should be applicable in practice. On some occasions, the first criterion was not entirely fulfilled, but still we were justified in regarding our systems as being satisfactory.
statistics human sciences soft computing linguistic modeling approximate reasoning