Transposed letter effect are letter-position specific when detecting words, so our recognition of words is based on what letters it contains, where the letters are placed within that word and the length of the word itself. Another example is the bayesian reader model created by Norris (2006) which also assumes that the letters in a word are associated with their specific location. Many experiments (for example, Perea and Lupker, 2003) have shown if you use transposed-letter priming, (for example, priming judge with jugde) you will see a priming effect but if the prime is a word where two letters are changed to other
Most common words in English such as literary works, novels, academic journals, newspapers, magazines, Hansard's Parliamentary Debates, blogs, chat logs, and emails. Another English corpus that has been used to study word frequency is the Brown Corpus, which was compiled by researchers at Brown University in the 1960s. The researchers published their analysis of the Brown Corpus in 1967. Their findings were similar, but not identical, to the findings of the OEC analysis. According to "The Reading Teacher's Book of Lists", the first 25 words in the OEC make up about one-third of all printed material in English, and the first 100 words make up