I lost 2 points. I chose (c) for the answer as I thought that since both schools took the same percentage size of about 3% of the undergraduates and both had a proportion, p= 0.80, Johns Hopkins and Ohio State would have almost the same sampling variability. I forgot to take into account that each school had different numbers of undergraduates. However, the correct answer is (b). Since a simple random sample of about 3% of Ohio State is about (0.03 x 40,00) = 1,200, it has a larger sample than the (0.03 x 2,000) = 60 undergraduates that make up the simple random sample of about 3% of the undergraduates at Johns Hopkin, meaning Ohio State has smaller variability. Thus, the estimate from Johns Hopkins has more sampling variability than that from Ohio State since it has a smaller sample of 60 undergraduates, making …show more content…
Choice (a) is wrong. The estimate from Johns Hopkins cannot have less sampling variability since it has a smaller sample size (60) compared to Ohio State (1,200); only larger samples give a smaller spread. Choice (c) is untrue since the sample size of Johns Hopkins (60) is not the same size as Ohio State (1,200), so it is not possible for both schools to have the same sampling variability. Choice (d) would be wrong since it is possible to make a statement about the sampling variability of the two estimates, by using the given number of undergraduates and the provided sample sizes which made choice (b) true. Choice (e) would be untrue since as mentioned above, (b) is the correct answer due to the fact that smaller samples give a larger spread and larger samples give a smaller spread, and so the option for none of the answers to be the best
a. The time (in years) it takes a sample of students to graduate college (Mean)
The population sampled due to its specific nature i.e., college students, and college graduates would need to be contemplated in regards to the testing results as it is offered as a depiction of the general population.
6. Based on questions 3, 4, and 5 is the mean or median a better estimate for the parameter of interest? Explain your reasoning.
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.
In the eastern front of U.S. Civil War there were two men who stood above the rest. Robert E. Lee was the commanding general of the Army of Northern Virginia. Thomas J. "Stonewall" Jackson commanded the Army of the Shenandoah. The military genius of these two men was far beyond that of any Union or Confederate officer in the east. History tells us that Robert E. Lee was one of the greatest commanding officers in history. History only tells us that Jackson was brave and stood like a stonewall at the First Battle of Manassas Junction, but was Jackson as good a commander as Lee? While they had their similarities these two men were very different in the ways they commanded their armies, and the ways they saw could end the war in victory
5. Find the sample variance s2 for the following sample data. Round your answer to the nearest hundredth.
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
8. The people who make up this article is the students from 7 different universities. It was rather representative because they were from universities that were located across the US, not just from one specific area. This was a unsystematic selection procedure because they weren’t from specific groups or students, just casual students from the seven different universities which created a representative sample of a big population.
Paula England wanted to understand what the hooking up culture and sexuality was of college students and how it was gender based. This was her focus for her research and throughout her data she found some interesting things about the hookup culture of college students. A sample is a part of the population that represents the whole. Her sample size was 18 different universities where she gathered data, and could make inferences about the population of college students as a whole. There were two different sampling methods that were used to gather data from students, she had students use interviews and online surveys.
These surveys sample about 15,000 students each year spanning across the three grades under consideration. However, not every question is asked of every student. Certain questions are reserved for certain subsamples.
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
There is a hero and a villain in almost every fiction piece. A protagonist and an antagonist. Each with their own set of unique characteristics that make them exceedingly different, yet they have to be somewhat alike to make the story engaging. Sir Arthur Conan Doyle’s Sherlock Holmes and John Clay are perfect examples of this. Although they are vastly different characters one can not miss the obvious similarities between the pair. Holmes and Clay are both extremely intelligent, the best at what they do, and obtain alternating personalities.
2. A sample can be used to estimate a population parameter. How does the sample size affect the estimate? If the sample is larger, what will this do to the error E?
In the survey, each of the questions is broken down into definitions of a specific scientific field. The control group has the correct numbers of men and women in the field, which we expect to line up with the actual information for each scientific field. The experimental number has skewed numbers of men and women in each of the scientific fields which will result in different answers, predominantly for the questions regarding the field of Macroeconomics, Earth Science, and Political Science. Each group (control and experimental) has 107 participants for a total of 214 participants. Below are the expected results for each group. An alpha level of
My population size is children aged eleven to sixteen residing in the United Kingdom and the Republic of Ireland. I have employed a sample size of thirty male and thirty female students aged eleven to sixteen; I had chosen this sample size because I had identified a calculation which would be perfect on helping to have a range of participants and therefore I could have a good medium sized sample, my research indicated that the average pupils enrolled at a secondary school is roughly three point six million pupils, so if I divide it by six thousand, then that would equal sixty and later on I can multiply it by six thousand and represent my data on behalf of all pupils in the United Kingdom and the Republic of Ireland and thus allowing my data to be more reliable and a better representation of eleven to sixteen residing in the United Kingdom and the Republic of Ireland.