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
Word ladder be connected with a word ladder. Knuth used a fixed collection of 5,757 of the most common English five-letter words, excluding proper nouns. He determined exactly when two words of the collection had a word ladder between them via other words in the collection. Knuth found that most words were connected to each other, and he also found that 671 words of the collection did not form a word ladder with any other words. He called these words "aloof", because "aloof" is itself an example of such a word. Word ladder Word ladder (also known as Doublets, word-links, change-the-word puzzles,