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The thickness (in millimeters) of the coating applied to disk drives is a characteristic that determines the usefulness of the product. When no unusual circumstances are present, the thickness (x) has a normal distribution with a mean. of 3 mm and a standard deviation of 0.05 mm. Suppose that the process will be monitored by selecting a random sample of 16 drives from each shift's production and determining the mean coating thickness for the sample. a. Describe the sampling distribution of (for a sample of size 16). b. When no unusual circumstances are present, we expect to be within the desired value. An value farther from 3 than is interpreted as an indication of a problem that needs attention. Compute (A plot over time of values with horizontal lines drawn at the limits is called a process control chart.) c. Referring to Part (b), what is the probability that a sample mean will be outside just by chance (i.e., when there are no unusual circumstances)? 0.0026 d. Suppose that a machine used to apply the coating is out of adjustment, resulting in a mean coating thickness of 3.05 mm. What is the probability that a problem will be detected when the next sample is taken? (Hint: This will occur if 3.05.) 0.8413 The thickness (in millimeters) of the coating applied to disk drives is a characteristic that determines the usefulness of the product. When no unusual circumstances are present, the thickness (x) has a normal distribution with a mean. of 3 mm and a standard deviation of 0.05 mm. Suppose that the process will be monitored by selecting a random sample of 16 drives from each shift's production and determining the mean coating thickness for the sample. a. Describe the sampling distribution of (for a sample of size 16). b. When no unusual circumstances are present, we expect is called a process control chart.) c. Referring to Part (b), what is the probability that a sample mean will be outside just by chance (i.e., when there are no unusual circumstances)? 0.0026 d. Suppose that a machine used to apply the coating is out of adjustment, resulting in a mean coating thickness of 3.05 mm. What is the probability that a problem will be detected when the next sample is taken? (Hint: This will occur if 3.05.) 0.8413 x\overline{x}

An experiment was conducted to evaluate the effect of decreases in frontalis muscle tension on headaches. The number of headaches experienced in a 2-week baseline period was recorded in nine subjects who had been experiencing tension headaches. Then the subjects were trained to lower frontalis muscle tension using biofeedback, after which the number of headaches in another 2-week period was again recorded. The data are again shown here. In that problem, the sampling distribution of was assumed to be normally distributed, and the analysis was conducted using the t test. For this problem assume the t test cannot be used because of an extreme violation of its normality assumption. Use the Wilcoxon signed ranks test to analyse the data. What do you conclude, using α\alpha=0.052 tail? Reference problem: Since muscle tension in the head region has been associated with tension headaches, you reason that if the muscle tension could be reduced, perhaps the headaches would decrease or go away altogether. You design an experiment in which nine subjects with tension headaches participate. The subjects keep daily logs of the number of headaches they experience during a 2-week baseline period. Then you train them to lower their muscle tension in the head region, using a biofeedback device. For this experiment, the biofeedback device is connected to the frontalis muscle, a muscle in the forehead region. The device tells the subject the amount of tension in the muscle to which it is attached (in this case, frontalis) and helps them achieve low tension levels. After 6 weeks of training, during which the subjects have become successful at maintaining low frontalis muscle tension, they again keep a 2-week log of the number of headaches experienced. The following are the numbers of headaches recorded during each 2-week period.

Subject No.BaselineAfter training117321373624535566102781860972\begin{matrix} \text{Subject No.} & \text{Baseline} & \text{After training}\\ \text{1} & \text{17} & \text{3}\\ \text{2} & \text{13} & \text{7}\\ \text{3} & \text{6} & \text{2}\\ \text{4} & \text{5} & \text{3}\\ \text{5} & \text{5} & \text{6}\\ \text{6} & \text{10} & \text{2}\\ \text{7} & \text{8} & \text{1}\\ \text{8} & \text{6} & \text{0}\\ \text{9} & \text{7} & \text{2}\\ \end{matrix}

a. Using α\alpha=0.052 tail, what do you conclude? Assume the sampling distribution of the mean of the difference scores (D) is normally distributed. Assume a non directional hypothesis is appropriate, because there is insufficient empirical basis to warrant a directional hypothesis. b. If the sampling distribution of D is not normally distributed, what other test could you use to analyze the data? What would your conclusion be? No of Headaches. D\overline { D }

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The results of a 2013 Adobe Systems study on retail apps and buying habits reveal insights on perceptions and attitudes toward mobile shopping using retail apps and browsers, providing new direction for retailers to develop their digital publishing strategies. Increased consumer interest in using shopping applications means retailers must adapt to meet the rising expectations for specialized mobile shopping experiences. The results indicate that tablet users (55percent) are almost twice as likely as smartphone users (28 percent) to use their device to purchase products and services. The findings also reveal that retail and catalog apps are rapidly catching up to mobile browsers as a viable shopping channel: nearly half of all mobile shoppers are interested in using apps instead of a mobile browser (45 percent of tablet shoppers and 49 percent of smartphone shoppers). The research is based on an online survey with a sample of 1,003 consumers. Identify potential concerns with coverage, nonresponse, sampling, and measurement errors.

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Answered 1 year ago

The results are based on an online survey.
The sample size is N=1,003N = 1,003 consumers.

As stated in the example, more tablet users use their devices for online shopping, therefore, coverage error could occur because the selection of individuals could include more tablet users than smartphone users in the favor of results.
Online surveys usually result in a lower response rate, therefore, there is a nonresponse error.
We don't have information about the size of the frame and how the sample was collected. Therefore, sampling error cannot be established because we don't know whether the sample is random.
And measurement error could occur if an online survey contained biased questions which could guide the subjects in a certain (desirable) direction.

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