As part of the study on ongoing fright symptoms due to exposure to horror movies

Question

As part of the study on ongoing fright symptoms due to exposure to horror movies at a young age, the following table was presented to describe the lasting impact these movies have had during bedtime and waking life:

(a) What percent of the students have lasting waking-life symptoms? (Round your answer to two decimal places.)
%

(b) What percent of the students have both waking-life and bedtime symptoms? (Round your answer to two decimal places.)
%

(c) Test whether there is an association between waking-life and bedtime symptoms. State the null and alternative hypotheses. (Use = 0.01.)

Null Hypothesis:

H0: Bedtime symptoms cause waking symptoms.

H0: Waking symptoms cause bedtime symptoms.     

H0: There is no relationship between waking and bedtime symptoms.

H0: There is a relationship between waking and bedtime symptoms.

Alternative Hypothesis:

Ha: Waking symptoms cause bedtime symptoms.

Ha: Bedtime symptoms cause waking symptoms.     

Ha: There is a relationship between waking and bedtime symptoms.

Ha: There is no relationship between waking and bedtime symptoms.

State the 2 statistic and the P-value. (Round your answers for 2 and the P-value to three decimal places.)

Conclusion:

We have enough evidence to conclude that there is a relationship.

We do not have enough evidence to conclude that there is a relationship.

     Waking
symptoms Bedtime symptoms Yes      No Yes 34 34 No 32 19

Explanation / Answer

a)percent of the students have lasting waking-life symptoms=(34+32)*100/119 =55.46%

b)percent of the students have both waking-life and bedtime symptoms=34*100/119 =28.57%

c)Null Hypothesis:H0: There is no relationship between waking and bedtime symptoms.

Alternative Hypothesis:Ha: There is a relationship between waking and bedtime symptoms.

applying chi square goodness of ft test:

X2=1.916

df=1

p vlaue=0.166

as p value is higher

We do not have enough evidence to conclude that there is a relationship.

Observed O Yes(walking No(walking Total Yes(bed time) 34 34 68 No(bed time) 32 19 51 Total 66 53 119 Expected E=rowtotal*column total/grand total Yes(walking No(walking Total Yes(bed time) 37.714 30.286 68 No(bed time) 28.286 22.714 51 Total 66 53 119 chi square =(O-E)^2/E Yes(walking No(walking Total Yes(bed time) 0.366 0.456 0.821 No(bed time) 0.488 0.607 1.095 Total 0.854 1.063 1.916

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