[janemorales]

Did I answer these correctly?

True 1.A simple random sample is formulated in such a manner that each item or person in the population has an equal chance of being included in the sample.

False 2.If nonprobability methods are used, not all items or people have a chance of being included in the sample.

True 3.If 40 samples, each of size n=21, were selected from a population of 22,493, we would expect the mean of the sample means and the population mean to be close but not exactly equal.

False 4.A sample of union members was selected and their opinions regarding the proposed management union contract were recorded with 160 out of the 200 members favored the proposed contract. A 95 percent confidence interval for the population proportion ranged from 0. 74 and 0. 85. If the sample were larger, this interval would be larger (wider).

True 5.Surveys from all members of a population are arranged in a file drawer alphabetically by date received. A random starting point is selected and then every nth member of the population is selected for the sample. This sampling is and example of simple random sampling.

False 6.If the size of a sample equals the size of the population, we would not expect any error in estimating the population parameter.

True 7.We can expect some difference between sample statistics and the corresponding population parameters. This difference is called the sampling error.

True 8.A sampling distribution of the means is a probability distribution listing all possible sample means of a given sample size selected from a population and the probability of occurrence associated with each sample mean.

False 9.If nonprobability sampling methods are used, the results may be biased.

True 10.The Central Limit Theorem states that if all samples of a particular size are selected from any population, the sampling distribution of the sample means is approximately a normal distribution.

True 11.The Central Limit Theorem states that if the sample size n is sufficiently large, the sampling distribution of the means will be approximately normal no matter whether the population is normally distributed, skewed, or uniform.

True 12.It is often not feasible to study the entire population because it is impossible to check all the items in the population.

True 13.The 95 percent confidence interval states that 95 percent of the sample means of a specified sample size selected from a population will lie within plus and minus 1. 96 standard deviations of the hypothesized population mean.

False 14.An estimate of the population mean based on a large sample is less reliable than an estimate made using a small sample.

False 15.The standard error of the mean will vary according to the size of the sample. As the sample size gets larger, the variability of the sample means gets smaller.

False 16.One misconception about the number to sample is that a larger sample of voters must be selected from a heavily populated state, such as New York, than from a small state such as Nevada.

True 17.The population of interest in your study is spread over a very large geographic area. To control the cost of sampling this population you might employ cluster sampling.

[Palkie84]

What is the difference between a sample mean and the population mean called?
A. Standard error of the mean
B. Sampling error
C. Interval estimate
D. Point estimate

[Karagyozi]

Was the solution to this ever updated?