/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Q37E The accompanying data on cube co... [FREE SOLUTION] | 91影视

91影视

The accompanying data on cube compressive strength (MPa) of concrete specimens appeared in the article 鈥淓xperimental Study of Recycled Rubber-Filled High-Strength Concrete鈥 (Magazine of Concrete Res., 2009: 549鈥556):

\(\begin{array}{l}112.3 97.0 92.7 86.0 102.0\\99.2 95.8 103.5 89.0 86.7\end{array}\)

a. Is it plausible that the compressive strength for this type of concrete is normally distributed?

b. Suppose the concrete will be used for a particular application unless there is strong evidence that true average strength is less than \(100MPa\). Should the concrete be used? Carry out a test of appropriate hypotheses.

Short Answer

Expert verified

(a) It is plausible.

(b) The concrete can be used.

Step by step solution

01

Define p-value in hypothesis testing.

The null hypothesis states that the population mean is equal to the value mentioned in the claim. If the null hypothesis is the claim, then the alternative hypothesis states the opposite of the null hypothesis.

\(\begin{array}{l}{H_0}:\mu = 0\\{H_a}:\mu \ne 0\end{array}\)

The formula for the value of the test statistic is given by, \(t = \frac{{\bar x - {\mu _0}}}{{s/\sqrt n }}\).

02

Assumption for test the appropriate hypothesis.

(a)

NORMAL PROBABILITY PLOT:

The horizontal axis shows the data values, while the vertical axis shows the standardised normal scores.

The standardised normal scores are the z-scores in the normal probability table in the appendix corresponding to an area of \(\frac{{j - 0.5}}{n}\) (or the closest area) with \(j \in \{ 1,2,3,...,n\} \) if the data comprises n data values. The least standardised score correlates to the smallest data value, and so on.

The population distribution is essentially normal if the pattern in the normal probability plot is roughly linear and does not contain strong curvature.

Because the normal probability plot has little curvature and is essentially linear, the compressive strength of this type of concrete is likely to be normally distributed.

03

Test the appropriate hypothesis.

(b)

The mean is the ration of sum of all values and the total number of values.

\(\begin{aligned}{c}\bar x &= \frac{{112.3 + 97 + 92.7 + ... + 103.5 + 89 + 86.7}}{{10}}\\ &= \frac{{964.2}}{{10}}\\ &\approx 96.42\end{aligned}\)

The square of the variance is the standard deviation.

\(\begin{aligned}{c}s &= \sqrt {\frac{{{{(112.3 - 96.42)}^2} + \ldots . + {{(86.7 - 96.42)}^2}}}{{10 - 1}}} \\ &\approx 8.2586\end{aligned}\)

Let the given be:

\(\begin{array}{l}n = 10\\\alpha = 0.05\end{array}\)

Claim that the true average strength is less than\(100MPa\).

The value of the test statistic:

\(\begin{aligned}{c}t &= \frac{{\bar x - {\mu _0}}}{{s/\sqrt n }}\\ &= \frac{{96.42 - 100}}{{8.2586/\sqrt {10} }}\\ &\approx - 1.371\end{aligned}\)

The P-value is the chance of getting the test statistic's result, or a number that is more severe. The P-value is the number (or interval) in the column header of the T table in the appendix that contains the t-value in the row\(\begin{array}{c}df = n - 1\\ = 10 - 1\\ = 9\end{array}\)for the student.

\(P > 0.10\)

As the P-value is smaller than the significance level, so the null hypothesis is rejected.

\(P > 0.05 \Rightarrow Fail to Reject {H_0}\)

The true average strength is less than \(100MPa\) is supported by appropriate evidence. Hence, the concrete can be used.

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91影视!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Many older homes have electrical systems that use fuses rather than circuit breakers. A manufacturer of 40-amp fuses wants to make sure that the mean amperage at which its fuses burn out is in fact 40. If the mean amperage is lower than 40, customers will complain because the fuses require replacement too often. If the mean amperage is higher than 40, the manufacturer might be liable for damage to an electrical system due to fuse malfunction. To verify the amperage of the fuses, a sample of fuses is to be selected and inspected. If a hypothesis test were to be performed on the resulting data, what null and alternative hypotheses would be of interest to the manufacturer? Describe type I and type II errors in the context of this problem situation.

In Problems \(19\) and \(20\) verify that the indicated expression is an implicit solution of the given first-order differential equation. Find atleast one explicit solution \(y = \phi (x)\) in each case. Use a graphing utility to obtain the graph of an explicit solution. Give an interval \(I\) of definition of each solution \(\phi \).

For the following pairs of assertions, indicate which with our rules for setting up hypotheses and why (the subscripts 1 and 2 differentiate between quantities for two different populations or samples):

a. H0: 碌= 100, Ha: 碌 > 100

b.H0: 蟽= 20, Ha: \(\sigma \le 20\)

c.H0: p鈮 .25, Ha: p= .25

d.H0: 碌1 - 碌2 = 25, Ha: 碌1 - 碌2 > 100

e.H0: \(S_1^2 = S_2^2\) , Ha: \(S_1^2 \ne S_2^2\)

f.H0: 碌= 120, Ha: 碌= 150

g.H0: 蟽1,/蟽2 =1,Ha: 蟽1,/ 蟽2 鈮1

h.H0p1 鈥 p2 = -.1, Ha: p1 鈥 p2 < -.1

The article 鈥淯ncertainty Estimation in Railway Track Life-Cycle Cost鈥 (J. of Rail and Rapid Transit, 2009) presented the following data on time to repair (min) a rail break in the high rail on a curved track of a certain railway line.

\(159 120 480 149 270 547 340 43 228 202 240 218\)

A normal probability plot of the data shows a reasonably linear pattern, so it is plausible that the population distribution of repair time is at least approximately normal. The sample mean and standard deviation are \(249.7\) and \(145.1\), respectively.

a. Is there compelling evidence for concluding that true average repair time exceeds \(200\) min? Carry out a test of hypotheses using a significance level of \(.05\).

b. Using \(\sigma = 150\), what is the type II error probability of the test used in (a) when true average repair time is actually \(300\) min? That is, what is \(\beta (300)\)?

Have you ever been frustrated because you could not get a container of some sort to release the last bit of its contents? The article 鈥淪hake, Rattle, and Squeeze: How Much Is Left in That Container?鈥 (Consumer Reports, May 2009: 8) reported on an investigation of this issue for various consumer products. Suppose five \(6.0oz\) tubes of toothpaste of a particular brand are randomly selected and squeezed until no more toothpaste will come out. Then each tube is cut open and the amount remaining is weighed, resulting in the following data (consistent with what the cited article reported):

\(.53,.65,.46,.50,.37.\)

Does it appear that the true average amount left is less than \(10\% \) of the advertised net contents?

a. Check the validity of any assumptions necessary for testing the appropriate hypotheses.

b. Carry out a test of the appropriate hypotheses using a significance level of \(.05\). Would your conclusion change if a significance level of \(.01\) had been used?

c. Describe in context type I and II errors, and say which error might have been made in reaching a conclusion.

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.