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How bad is the wireless network at JJ? Out of a random sample of 123 J1 students

ID: 3318255 • Letter: H

Question

How bad is the wireless network at JJ? Out of a random sample of 123 J1 students, 75 students said they had a network connection at J1 lost in the past month. Let p be the (unknown) true proportion 3 students who have lost a network connection in the last month. Let phat be the sample proportion a)Obtain an unbiased point estimate of p. b) we wish to construct a 96 % classical confidence interval forp. what is the critical value multiplier zstar c) Create a 96% classical confidence interval for p? d) How long is the 96% classical confidence interval for p? f) Based on this data estimate the standard deviation of the sample proportion of 11 students who lost a connection in the last month. g)Assuming the same value of the sample proportion what is the smallest sample size for which the length of the 96% confidence interval for p is less than or equal to .12?

Explanation / Answer

TRADITIONAL METHOD

a.

given that,

possibile chances (x)=75

sample size(n)=123

success rate ( p )= x/n = 0.6098

I.

sample proportion = 0.6098

standard error = Sqrt ( (0.6098*0.3902) /123) )

= 0.044

II.

margin of error = Z a/2 * (stanadard error)

where,

b.

Za/2 = Z-table value

level of significance, = 0.04

from standard normal table, two tailed z /2 =2.054

margin of error = 2.054 * 0.044

= 0.0903

c.

III.

CI = [ p ± margin of error ]

confidence interval = [0.6098 ± 0.0903]

= [ 0.5194 , 0.7001]

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DIRECT METHOD

given that,

possibile chances (x)=75

sample size(n)=123

success rate ( p )= x/n = 0.6098

CI = confidence interval

confidence interval = [ 0.6098 ± 2.054 * Sqrt ( (0.6098*0.3902) /123) ) ]

= [0.6098 - 2.054 * Sqrt ( (0.6098*0.3902) /123) , 0.6098 + 2.054 * Sqrt ( (0.6098*0.3902) /123) ]

= [0.5194 , 0.7001]

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interpretations:

1. We are 96% sure that the interval [ 0.5194 , 0.7001] contains the true population proportion

2. If a large number of samples are collected, and a confidence interval is created

for each sample, 96% of these intervals will contains the true population proportion

d.

standard Deviation ( sd )= sqrt(PQ/n) = sqrt(0.609756097560976*0.3902/123)

=0.044

e.

Compute Sample Size ( n ) = n=(Z/E)^2*p*(1-p)

Z a/2 at 0.04 is = 2.054

Sample Proportion = 0.6098

ME = 0.12

n = ( 2.054 / 0.12 )^2 * 0.6098*0.3902

= 69.7129 ~ 70

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