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UNO [17]
1 year ago
12

A sample of 81 tobacco smokers who recently completed a new smoking-cessation program were asked to rate the effectiveness of th

e program on a scale of 1 to 10, with 10 corresponding to "completely effective" and 1 corresponding to "completely ineffective". The average rating was 5.6 and the standard deviation was 4.6. Construct a 95% confidence interval for the mean score. 5.2 < μ < 6.0 0 < μ < 5.6 4.6 < μ < 6.6 5.1 < μ < 6.1
Mathematics
1 answer:
Kruka [31]1 year ago
4 0

Answer:

95% confidence interval for the true mean score is [4.6 , 6.6].

Step-by-step explanation:

We are given that a sample of 81 tobacco smokers who recently completed a new smoking-cessation program were asked to rate the effectiveness of the program on a scale of 1 to 10.

The average rating was 5.6 and the standard deviation was 4.6.

Firstly, the pivotal quantity for 95% confidence interval for the true mean is given by;

                      P.Q. =  \frac{\bar X-\mu}{\frac{s}{\sqrt{n} } }  ~ t_n_-_1

where, \bar X = sample average rating = 5.6

            s = sample standard deviation = 4.6

            n = sample of tobacco smokers = 81

            \mu = population mean score

<em>Here for constructing 95% confidence interval we have used One-sample t test statistics as we don't know about population standard deviation.</em>

<u>So, 95% confidence interval for the population mean score, </u>\mu<u> is ;</u>

P(-1.993 < t_8_0 < 1.993) = 0.95  {As the critical value of t at 80 degree of

                                            freedom are -1.993 & 1.993 with P = 2.5%}  

P(-1.993 < \frac{\bar X-\mu}{\frac{s}{\sqrt{n} } } < 1.993) = 0.95

P( -1.993 \times {\frac{s}{\sqrt{n} } } < {\bar X-\mu} < 1.993 \times {\frac{s}{\sqrt{n} } } ) = 0.95

P( \bar X-1.993 \times {\frac{s}{\sqrt{n} } } < \mu < \bar X+1.993 \times {\frac{s}{\sqrt{n} } } ) = 0.95

<u>95% confidence interval for</u> \mu = [ \bar X-1.993 \times {\frac{s}{\sqrt{n} } } , \bar X+1.993 \times {\frac{s}{\sqrt{n} } } ]

                                            = [ 5.6-1.993 \times {\frac{4.6}{\sqrt{81} } } , 5.6+1.993 \times {\frac{4.6}{\sqrt{81} } } ]

                                            = [4.6 , 6.6]

Therefore, 95% confidence interval for the true mean score is [4.6 , 6.6].

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we know that

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In this problem

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Researchers have a sample size of 24 , and they are using the Student's t-distribution. What are the degrees of freedom and how
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For this case assuming that the random variable is X

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And we notate the distribution we got: X \sim t_{n-1}= t_{23}

Step-by-step explanation:

Previous concepts

The t distribution (Student’s t-distribution) is a "probability distribution that is used to estimate population parameters when the sample size is small (n<30) or when the population variance is unknown".

The shape of the t distribution is determined by its degrees of freedom and when the degrees of freedom increase the t distirbution becomes a normal distribution approximately.  

The degrees of freedom represent "the number of independent observations in a set of data. For example if we estimate a mean score from a single sample, the number of independent observations would be equal to the sample size minus one."

Solution to the problem

For this case assuming that the random variable is X

df = n-1

And replacing n = 24 we got:

df = 24-1=23

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Step-by-step explanation:

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12 ,14, 16 , 19, 21 , 22 , 28 , 32

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Also calculating the standard variation in order to know the spread , we need to first of all calculate the mean

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Therefore to calculate the standard deviation, we need to calculate the variance, which  is

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Marta_Voda [28]
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20
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