KFUPM |Term 041 |Date: 25/12/2004 | |
|Mathematical Sciences |STAT 211 |Duration: 10 minutes |
| |Quiz# 7 | |
|Name: |ID#: |Section#: |Serial#: |
Show your work in detail and write neatly and eligibly
1. A 95 percent confidence interval estimate will have a margin of error that is approximately + 95 percent of the size of the population mean.
Answer: False
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Given this information, what sample size was used to arrive at this estimate? a. About 344. b. Approximately 1,066. c. Just under 700. d. Can’t be determined without more information.
Answer: B
With My Best Wishes
|KFUPM |Term 041 |Date: 25/12/2004 |
|Mathematical Sciences |STAT 211 |Duration: 10 minutes |
| |Quiz# 7 | |
|Name: |ID#: |Section#: 1 2 4 |Serial#: |
Show your work in detail and write neatly and eligibly
1. All other factors held constant, the higher the confidence level, the closer the point estimate for the population mean will be to the true population mean.
Answer: False
2. In estimating a population mean, increasing the confidence level will result in a higher margin of error for a given sample
2. The type of “lust murderer” who is usually of above-average intelligence, methodical and cunning, and socially skilled, and who tricks victims into situations in which he can torture and then murder them, is called a(n),
6. Based on questions 3, 4, and 5 is the mean or median a better estimate for the parameter of interest? Explain your reasoning.
b. Construct a 91.5% confidence interval for the mean time it take for all workers who are employed in downtown Toronto
12. _____ For a given population, confidence intervals constructed from larger samples tend to be narrower than those constructed from smaller samples. Which statement below best describes why this is true? (A) The variability of the sample mean is less for larger samples. (B) The z-value for larger samples tends to be more accurate. (C) The population variance is larger for large populations. (D) As the sample size increases, the z-value (or t-value) becomes smaller. A machine dispenses potato chips into bags that are advertised as containing one pound of product. To be on the safe side, the machine is supposed to be calibrated to dispense 16.07 ounces per bag, and from long time observation, the distribution of the fill-weights is known to be approximately normal and the process is known to have a standard deviation of 0.15 ounces.
If the population was distributed normally the sample size to be taken will decrease. As the population normally distributes the variance and standard deviation population means will decrease so less number of sample would be appropriate to give good estimates of disease severity to determine the disease epidemics.
Population A and Population B both have a mean height of 70.0 inches with an SD of 6.0. A random sample of 30 people is picked from population A, and random sample of 50 people is selected from Population B. Which sample mean will probably yield a more accurate estimate of its population mean? Why? Despite, both Population A and Population having a mean height of 70.0 inches with an SD of 6.0, Population B will
Description / Instructions: Complete the following Week 1 Assignment in WileyPLUS: * Exercise 8-4 * Exercise 8-11 * BYP 8-1 * BYP 8-2
The margin of error is 2%, “that is the amount of error that the CEO finds acceptable for him” (The Importance and Effect of Sample Size) (2016). If 90% of the people that were surveyed said yes, and 10% answer no, the CEO tolerance level for error might be able to be increased the it being 50/50. The confidence level that is trying to be reached by the CEO is 95.44. The confidence level is the doubt the CEO will tolerate. Let’s say the CEO has 30 yes or no questions on his survey. Having a confidence level of 95%,
The data sets for problems 5 and 6 can be found through the Pearson Materials in the Student Textbook Resource Access link, listed under Academic Resources. The data is listed in the data file named Lesson 20 Exercise File 1. Answer Exercises 5 and 6 based on the following research problem:
The customers in this case study have complained that the bottling company provides less than the advertised sixteen ounces of product. They need to determine if there is enough evidence to conclude the soda bottles do not contain sixteen ounces. The sample size of sodas is 30 and has a mean of 14.9. The standard deviation is found to be 0.55. With these calculations and a confidence level of 95%, the confidence interval would be 0.2. There is a 95% certainty that the true population mean falls within the range of 14.7 to 15.1.
A field researcher is gathering data on the trunk diameters of mature pine and spruce trees in a certain area. The following are the results of his random sampling. Can he conclude, at the .10 level of significance, that
As pointed out in the course text, point estimates only provide information about the difference or association between groups. It is not possible to determine the level of accuracy of these estimates because bias may occur in the estimation. In particular, errors may arise in research due to sampling, an inadequate sampling frame, improperly designed research instruments or non-response. While a researcher can minimize bias in research by enhancing the design, sampling errors are inevitable as they result from chance (Explorable.com, 2009). Therefore, the likelihood that a point estimate is accurate is minimal. In this context, confidence intervals suffice to provide a range of values within which one is likely to find the population parameter with a specified probability level. The confidence interval are very useful, particularly in a business context
Confidence intervals (CI) describe the amount of uncertainty associated with a sample estimate of a population parameter. The narrower the range, the more precise the study’s estimates, and the more confident you can be in the “real finding” and not due to chance. This is expressed in terms of 95% CI which represents the range of results within which we can be 95% certain that the true will be revealed. To illustrate how confidence intervals can help, suppose that a 90% confidence interval states that the population mean is greater than 100 and less than 200. Suppose we used the same sampling method to select different sample and compute a different interval estimate for each sample. Some interval estimates would include the true population
2. Because there 's more precision involved in estimating the mean of a distribution than in predicting a particular observation from that distribution, we would expect the confidence interval to be narrower than the prediction interval. We can verify this by comparing the formulas for computing the intervals (shown near the top). As noted previously, the only difference between the prediction interval formula and the confidence interval formula is that the prediction interval formula has a [pic] in the sum underneath the square root, while the confidence interval formula does not. This makes the margin of error (the term following the "[pic]") greater in the prediction interval formula than in the confidence interval formula, which means that the
For example, using Table 1 above, it can be said with 99% confidence that if any random detached house is chosen from the entire population, it will be within the price range of £264,817 to £382,503. Using 99% rather than 95% means that