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8. A one-tailed hypothesis test with the t statistic Antisocial personality diso

ID: 2908375 • Letter: 8

Question

8. A one-tailed hypothesis test with the t statistic Antisocial personality disorder (ASPD) is characterized by deceitfulness, reckless disregard for the wll-being of others, a diminished capacity for remorse, superficial charm, thrill seeking, and poor behavioral control. ASPD is not normally diagnosed in children or adolescerts, but artsocia tendendes?n sometimes be recognized in cidhood or early adolescence iames Blair and his leagues have studied the ability of chidren with antisociai tendendies to recognize facial expressions that depict sadness, happiness, anger, disgust, fear, and surprise. They have found that chidren with antisocial tendendies have selective impairments, with significantly more difficulty recognizing fearful and sad expressions Suppose you have a sampie of 35 14-year-ald chidren with antisocia tendencies and you are particulary interested in the emotion of disgust. The average 14-year-old has a score on the emotion recognition scale of 13.10. (The higher the score on this scale, the mcre strongly an emotion). Assume that scores on the emation recognidion scale are normally distributed to be correctly ident ied. Therefore, higher scores indicate greater difficuity recognizing the You believe that children with antisocial tendendes will have a harder time recogniring the emotion of disgust (in other words, they will have higher scores on the emation recognition test) What is your nall hypothesis stated using symbols? What is your aternative hypothesis stated using symbols? tailed test. Given what you know, you will evaluate this hypothesis using a statistic This is a using the Distributions tool, locate the critical region for a 0 Degrees of Freedom 33 search DELL

Explanation / Answer

null : mu = 13.10
alernate : mu > 13.10
this is right tailed test
using t-statistics

df = n-1 = 35-1 = 34
t-critical = t.inv(0.95,34)
= 1.690924255
standard error = sd/sqrt(n) = 4.63/sqrt(35)
=0.78261283987

t-statistic = (Xbar - mu)/(sd/sqrt(n))
= (14.35 - 13.10)/(4.63/sqrt(35))
= 1.59721376434

since TS does not lie in critical
we fail to

there is not

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