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The article “Concrete Pressure on Formwork” (Mag. of Concrete Res., 2009: 407–417) gave the following observations on maximum concrete pressure (kN/m2 ):

33.2 41.8 37.3 40.2 36.7 39.1 36.2 41.8

36.0 35.2 36.7 38.9 35.8 35.2 40.1

a.Is it plausible that this sample was selected from a normal population distribution?

b. Calculate an upper confidence bound with confidence level 95% for the population standard deviation of maximum pressure.

Short Answer

Expert verified

a) Yes, It is plausible.

b) The upper confidence bound with confidence level of \(95\% \) for \(\sigma \) is \(1.834\).

Step by step solution

01

Step 1:Sample variance and Sample deviation:

The sample variance\({s^2}\)is \({s^2} = \frac{1}{{n - 1}} \cdot {S_{xx}}\)

Where

\(\begin{array}{l}{S_{xx}} = \sum {({x_i} - \overline x } {)^2}\\ = \sum {{x_i}^2} - \frac{1}{n} \cdot {\left( {\sum {{x^i}} } \right)^2}\end{array}\)

The sample standard deviation \(s\)is,\(s = \sqrt {{s^2}} \),

\(s = \sqrt {\frac{1}{{n - 1}} \cdot {S_{xx}}} \)

02

Solution for part a).

From the normal probability plot, we can say that it is plausible that the sample was taken from a normal population distribution.

03

Solution for part b).

An upper confidence bound for standard deviation with confidence level \(100(1 - \alpha )\% \) can be computed using formula

\(\sqrt {\frac{{(n - 1){s^2}}}{{{X^2}_{1 - \alpha ,n - 1}}}} \)

Using the standard variance and standard deviation formulas, it is easy to obtain the sample standard deviation, and it is,

\(s = 1.579\)

There are total of \(n = 15\) observations.

In order to obtain \(95\% CI\) for \(\sigma \), value \(\alpha \)is needed and can be obtain as,

\(\begin{array}{l}100(1 - \alpha ) = 95\\\alpha = 0.05\end{array}\)

The only missing value for the upper confidence interval is,

\(\begin{array}{l}{X^2}_{1 - \alpha ,n - 1} = {X^2}_{0.95,14}\\{X^2}_{1 - \alpha ,n - 1} = 6.571\end{array}\)

Therefore, the upper confidence bound with confidence level of \(95\% \)for\(\sigma \) is

\(\begin{array}{l}\sqrt {\frac{{(n - 1){s^2}}}{{{X^2}_{1 - \alpha ,n - 1}}}} = \sqrt {\frac{{14(1.579)}}{{6.571}}} \\ = 1.834\end{array}\)

Hence, The upper confidence bound with confidence level of \(95\% \) for \(\sigma \) is \(1.834\)..

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Most popular questions from this chapter

Suppose that a random sample of \({\rm{50}}\) bottles of a particular brand of cough syrup is selected and the alcohol content of each bottle is determined. Let \({\rm{\mu }}\) denote the average alcohol content for the population of all bottles of the brand under study. Suppose that the resulting \({\rm{95\% }}\)confidence interval is \({\rm{(7}}{\rm{.8,9}}{\rm{.4)}}\). a. Would a \({\rm{90\% }}\) confidence interval calculated from this same sample have been narrower or wider than the given interval? Explain your reasoning. b. Consider the following statement: There is a \({\rm{95\% }}\) chance that \({\rm{\mu }}\) is between \({\rm{7}}{\rm{.8}}\) and \({\rm{9}}{\rm{.4}}\). Is this statement correct? Why or why not? c. Consider the following statement: We can be highly confident that \({\rm{95\% }}\) of all bottles of this type of cough syrup have an alcohol content that is between \({\rm{7}}{\rm{.8}}\) and \({\rm{9}}{\rm{.4}}\). Is this statement correct? Why or why not? d. Consider the following statement: If the process of selecting a sample of size \({\rm{50}}\) and then computing the corresponding \({\rm{95\% }}\) interval is repeated \({\rm{100}}\)times, \({\rm{95}}\) of the resulting intervals will include \({\rm{\mu }}\). Is this statement correct? Why or why not?

A state legislator wishes to survey residents of her district to see what proportion of the electorate is aware of her position on using state funds to pay for abortions.

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b. Calculate an upper prediction bound for the escape time of a single additional worker using a prediction level of \({\rm{95\% }}\). How does this bound compare with the confidence bound of part (a)?

c. Suppose that two additional workers will be chosen to participate in the simulated escape exercise. Denote their escape times by \({\rm{X27 and X28}}\), and let X new denote the average of these two values. Modify the formula for a PI for a single x value to obtain a PI for X new, and calculate a 95% two-sided interval based on the given escape data.

presented a sample of \({\rm{n = 153}}\)observations on ultimate tensile strength, the previous section gave summary quantities and requested a large-sample confidence interval. Because the sample size is large, no assumptions about the population distribution are required for the validity of the CI.

a. Is any assumption about the tensile-strength distribution required prior to calculating a lower prediction bound for the tensile strength of the next specimen selected using the method described in this section? Explain.

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