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Concept explainers
Material strength investigations provide a rich area of application for statistical meth ods.
The article “Effects of Aggregates and Microfillers on the Flexural Properties of
Concrete” (Magazine of Concrete Research, 1997: 81–98) reported on a study of
strength properties of high-performance concrete obtained by using superplasticizers
and certain binders. The compressive strength of such concrete had previously
been investigated, but not much was known about flexural strength (a measure of
ability to resist failure in bending). The accompanying data on flexural strength (in
MegaPascal, MPa, where 1 Pa (Pascal) 5 1.45 3 1024 psi) appeared in the article
cited:
5.9 7.2 7.3 6.3 8.1 6.8 7.0 7.6 6.8 6.5 7.0 6.3 7.9 9.0
8.2 8.7 7.8 9.7 7.4 7.7 9.7 7.8 7.7 11.6 11.3 11.8 10.7
Suppose we want an estimate of the average value of flexural strength for all beams
that could be made in this way (if we conceptualize a population of all such beams,
we are trying to estimate the population mean). It can be shown that, with a high
degree of confidence, the population mean strength is between 7.48 MPa and
8.80 MPa; we call this a confidence interval or
data could be used to predict the flexural strength of a single beam of this type. With
a high degree of confidence, the strength of a single such beam will exceed
7.35 MPa; the number 7.35 is called a lower prediction bound.
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- Young's modulus is a quantitative measure of stiffness of an elastic material. Suppose that for aluminum alloy sheets of a particular type, its mean value and standard deviation are 70 GPa and 1.6 GPa, respectively (values given in the article "Influence of Material Properties Variability on Springback and Thinning in Sheet Stamping Processes: A Stochastic Analysis" (Intl. J. of Advanced Manuf. Tech., 2010: 117–134)). (a) If X is the sample mean Young's modulus for a random sample of n = 16 sheets, where is the sampling distribution of X centered, and what is the standard deviation of the X distribution? E(X) = GPa ? X = GPa (b) Answer the questions posed in part (a) for a sample size of n = 64 sheets. E(X) = GPa ? X = GPa (c) For which of the two random samples, the one of part (a) or the one of part (b), is X more likely to be within 1 GPa of 70 GPa? Explain your reasoning. X is more likely to be within 1 GPa of the mean in part (a). This is due to…arrow_forward2. Consider a study where students are measured on whether they had an internship during their time at WKU (Y/N) and whether they had a job at graduation (Y/N). If we wanted to test whether having an internship was associated with having a job at graduation (i.e., internship holders were more likely to have jobs), why would the chi-square test be inappropriate for this hypothesis? How should we analyze our data?arrow_forwardRefer to Exercise 8.S.6. Analyze these data using a Wilcoxon signed-rank test.arrow_forward
- Young's modulus is a quantitative measure of stiffness of an elastic material. Suppose that for aluminum alloy sheets of a particular type, its mean value and standard deviation are 70 GPa and 1.6 GPa, respectively (values given in the article "Influence of Material Properties Variability on Springback and Thinning in Sheet Stamping Processes: A Stochastic Analysis" (Intl. J. of Advanced Manuf. Tech., 2010: 117-134)). (a) If X is the sample mean Young's modulus for a random sample of n = 64 sheets, where is the sampling distribution of X centered, and what is the standard deviation of the X distribution? E(X) ох = GPa GPa (b) Answer the questions posed in part (a) for a sample size of n = 256 sheets. E(X) GPa GPa ох = (c) For which of the two random samples, the one of part (a) or the one of part (b), is X more likely to be within 1 GPa of 70 GPa? Explain your reasoning. O X is more likely to be within 1 GPa of the mean in part (b). This is due to the increased variability of X that…arrow_forwardAn article contained the following observations on degree of polymerization for paper specimens for which viscosity times concentration fell in a certain middle range: 415 421 422 423 426 429 431 434 436 439 445 446 448 453 455 463 464 (a) Construct a boxplot of the data. O 420 420 430 430 440 440 450 The data appears to be centered near 438. The data is strongly skewed. There is one outlier. 450 Comment on any interesting features. (Select all that apply.) There are no outliers. The data appears to be centered near 428. There is little or no skew. 460 420 420 430 430 (b) Is it plausible that the given sample observations were selected from a normal distribution? Yes No 440 440 450 450 460 460 (c) Calculate a two-sided 95% confidence interval for true average degree of polymerization. (Round your answers to two decimal places.)arrow_forwardYoung's modulus is a quantitative measure of stiffness of an elastic material. Suppose that for aluminum alloy sheets of a particular type, its mean value and standard deviation are 70 GPa and 1.6 GPa, respectively (values given in the article "Influence of Material Properties Variability on Springback and Thinning in Sheet Stamping Processes: A Stochastic Analysis" (Intl. J. of Advanced Manuf. Tech., 2010: 117-134)). (a) If X is the sample mean Young's modulus for a random sample of n = 16 sheets, where is the sampling distribution of X centered, and what is the standard deviation of the X distribution? E(X) = GPa GPa x = (b) Answer the questions posed in part (a) for a sample size of n = 64 sheets. E(X) GPa GPa ox = (c) For which of the two random samples, the one of part (a) or the one of part (b), is X more likely to be within 1 GPa of 70 GPa? Explain your reasoning. O X is more likely to be within 1 GPa of the mean in part (b). This is due to the decreased variability of X that…arrow_forward
- Young's modulus is a quantitative measure of stiffness of an elastic material. Suppose that for aluminum alloy sheets of a particular type, its mean value and standard deviation are 70 GPa and 1.6 GPa, respectively (values given in the article "Influence of Material Properties Variability on Springback and Thinning in Sheet Stamping Processes: A Stochastic Analysis" (Intl. J. of Advanced Manuf. Tech., 2010: 117-134)). | If X is the sample mean Young's modulus for a random sample of n = 64 sheets, where is the sampling distribution of X centered, and what is the standard deviation of the X distribution? EX) = GPa GPa J Answer the questions posed in part (a) for a sample size of n = 256 sheets. E(X) = GPa GPa For which of the two random samples, the one part (a) or the one of part (b), is X more likely to be within 1 GPa of 70 GPa? Explain your reasoning. O X is more likely to be within 1 GPa of the mean in part (b). This is due to the increased variability of X that comes with a larger…arrow_forwardYoung's modulus is a quantitative measure of stiffness of an elastic material. Suppose that for aluminum alloy sheets of a particular type, its mean value and standard deviation are 70 GPa and 1.6 GPa, respectively (values given in the article "Influence of Material Properties Variability on Springback and Thinning in Sheet Stamping Processes: A Stochastic Analysis" (Intl. J. of Advanced Manuf. Tech., 2010: 117–134)). (a) If X is the sample mean Young's modulus for a random sample of n = 64 sheets, where is the sampling distribution of X centered, and what is the standard deviation of the X distribution? E(X) = GPa ? X = GPa (b) Answer the questions posed in part (a) for a sample size of n = 256 sheets. E(X) = GPa ? X = GPaarrow_forwardThe decline of salmon fisheries along the Columbia River in Oregon has caused great concern among commercial and recreational fishermen. The paper 'Feeding of Predaceous Fishes on Out-Migrating Juvenile Salmonids in John Day Reservoir, Columbia River' (Trans. Amer. Fisheries Soc. (1991: 405-420) gave the accompanying data on y = maximum size of salmonids consumed by a northern squaw fish (the most abundant salmonid predator) and x = squawfish length, both in mm. Here is the computer software printout of the summary: Coefficients: Estimate Std. Error t value Pr(> |t|) (Intercept) −89.010 16.703 −5.329 0.000 Length 0.705 0.046 15.293 0.000 Using this information, give the equation of the least squares regression line.arrow_forward
- 3.1.14 WP An article in Knee Surgery, Sports Traumatol- ogy, Arthroscopy ["Arthroscopic Meniscal Repair with an Absorbable Screw: Results and Surgical Technique" (2005, Vol. 13, pp. 273-279)] cited a success fac of more than 90% for meniscal tears with a rim width under 3 mm, but only a 67% success rate for tears of 3-6 mm. If you are unlucky enough to suffer a meniscal tear of under 3 mm on your left knee and one of width 3-6 mm on your right knee, what is the probability mass function of the number of successful surgerics? Assume that the surgeries are independent.arrow_forwardThe authors of the paper "Statistical Methods for Assessing Agreement Between Two Methods of Clinical Measurement"† compared two different instruments for measuring a person's ability to breathe out air. (This measurement is helpful in diagnosing various lung disorders.) The two instruments considered were a Wright peak flow meter and a mini-Wright peak flow meter. Seventeen people participated in the study, and for each person air flow was measured once using the Wright meter and once using the mini-Wright meter. Subject Mini-WrightMeter WrightMeter Subject Mini-WrightMeter WrightMeter 1 512 494 10 445 433 2 430 395 11 432 417 3 520 516 12 626 656 4 428 434 13 260 267 5 500 476 14 477 478 6 600 557 15 259 178 7 364 413 16 350 423 8 380 442 17 451 427 9 658 650 (a) Suppose that the Wright meter is considered to provide a better measure of air flow, but the mini-Wright meter is easier to transport and to use. If the two types of meters produce…arrow_forward(a) A research has been conducted an experiment to compare the deflection (um) between two types of material for cutting tool in milling machining process. About 30 samples of cutting tool for material A and 30 of cutting tool for material B has been used for during the test. Table 2(a) shows several descriptive statistics represent the data of tensile strength. 2 Table 2 (a) Descriptive statistics for deflection (um) Material Number Minimum Q1 median Q3 Маximum of value value specimen A 30 0.462 3.453 6.415 8.548 13.599 В 30 0.2 2.037 4.157 7.716 15.491 (i) Plot a box plot based on recorded data given in Table 2(a) (ii) Based on the box plot, which material of cutting tool is have better performance?State your reason (ii1) Suppose that material A produce deflection of 4.4 µum. The data is wrongly recorded as 44 um. What you can interpret about the box plot? (iv) Calculate the value of IQR for both materialsarrow_forward
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