Question:

In the article by Gadd and Phipps (2012), they refer to the challenges faced by psychological and, specifically, neuropsychological assessment. Their study focused on a preliminary standardisation of the Wisconsin Card Sorting Test (a non-verbal measure) for Setswana-speaking university students. The US normative sample is described as participants (N = 899) from both genders who were screened beforehand to exclude individuals with a history of neurological, learning, emotional and attention difficulties. The South African sample consisted of university students (N = 93) from both genders, between the ages of 18 and 29, who were screened in terms of hearing and visual impairments and any history of psychiatriceurological difficulties. The latter was done to prevent contamination of the results by these variables. The students were from the University of Limpopo, Medunsa Campus. Answer Questions 1 to 5.

Question 5

Gadd and Phipps (2012) found that the results of the South African sample on the Wisconsin Card Sorting Test did not resemble a normal distribution and could not be converted to a normal distribution. This implies that the ...

(1) mean performance of this sample cannot be calculated

(2) standard deviation will differ below and above the mean

(3) mean and standard deviation do not provide a predetermined distribution of performance

(4) results cannot be replicated

Would 1 be the correct answer?

A Markov chain with state space {1, 2, 3} has transition probability matrix 0.6 0.3 0.1\\ P. = 0.3 0.3 0.4 0.4 0.1 0.5 (a) Is this Markov chain irreducible? Is the Markov chain recurrent or transient? Explain your answers. (b) What is the period of state 1? Hence deduce the period of the remaining states. Does this Markov chain have a limiting distribution? (c) Consider a general three-state Markov chain with transition matrix P11 P12 P13 P = P21 P22 P23 P31 P32 P33 Give an example of a specific set of probabilities p;; for which the Markov chain is not irreducible (there is no single right answer to this, of course !).Problem 3. Consider the Markov chain shown in Figure 2. Figure 2: Problem 3 Markov chain 1. Let the initial distribution be Pr(A) : Pr(B) = 0.5. What is the probability distribution after one step? 2. What is the stationary distribution of the Markov chain