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Which of the following statements about sampling and estimation is most accurate?

A)	A confidence interval estimate consists of a range of values that bracket the parameter with a specified level of probability, 1 ? β.

B)	Time-series data are observations over individual units at a point in time.

C)	A point estimate is a single estimate of an unknown population parameter calculated as a sample mean.

Time-series data are observations taken at specific and equally-spaced points.
A confidence interval estimate consists of a range of values that bracket the parameter with a specified level of probability, 1 ? α.

Which of the following statements about sampling and estimation is most accurate?

A)	The probability that a parameter lies within a range of estimated values is given by α.

B)	The standard error of the sample means when the standard deviation of the population is unknown equals s / √n, where s = sample standard deviation.

C)	The standard error of the sample means when the standard deviation of the population is known equals σ / √n, where σ = sample standard deviation adjusted by n ? 1.

The probability that a parameter lies within a range of estimated values is given by 1 ? α. The standard error of the sample means when the standard deviation of the population is known equals σ / √n, where σ = population standard deviation.

A range of estimated values within which the actual value of a population parameter will lie with a given probability of 1 ? α is a(n):

A)	α percent confidence interval.

B)	(1 ? α) percent confidence interval.

C)	α percent point estimate.

A 95% confidence interval for the population mean (α = 5%), for example, is a range of estimates within which the actual value of the population mean will lie with a probability of 95%. Point estimates, on the other hand, are single (sample) values used to estimate population parameters. There is no such thing as a α percent point estimate or a (1 ? α) percent cross-sectional point estimate.

Which of the following characterizes the typical construction of a confidence interval most accurately?

A)	Point estimate +/- (Reliability factor x Standard error).

B)	Standard error +/- (Point estimate / Reliability factor).

C)	Point estimate +/- (Standard error / Reliability factor).

We can construct a confidence interval by adding and subtracting some amount from the point estimate. In general, confidence intervals have the following form:

Point estimate +/- Reliability factor x Standard error

Point estimate = the value of a sample statistic of the population parameter

Reliability factor = a number that depends on the sampling distribution of the point estimate and the probability the point estimate falls in the confidence interval (1 – α)

Standard error = the standard error of the point estimate

The range of possible values in which an actual population parameter may be observed at a given level of probability is known as a:

A confidence interval is a range of values within which the actual value of a parameter will lie, given a specified probability level. A point estimate is a single value used to estimate a population parameter. An example of a point estimate is a sample mean. The degree of confidence is the confidence level associated with a confidence interval and is computed as 1 ? a.