Exam 7: Understanding Data: Using Statistics for Inference and Estimation

A population has a mean of 50 and a standard deviation of 8. If samples of size N = 16 are randomly drawn from this population, then the standard error will be equal to.

The sampling distribution of the mean is.

The distribution of X values when all possible samples of size N are selected from a population is called a distribution of the mean.

You can be percent confident that an interval that includes the values between 1.96 standard errors below the sample mean and 1.96 standard errors above the sample mean will include the population mean.

A population has a mean of 70 and a standard deviation of 8. If samples of size N = 16 are randomly drawn from this population, then what proportion of sample means will fall between 66 to 74?

If you wish to increase the confidence level for the estimation of a parameter, then the .

The size of s X . is related to the variability of scores in the population and to the sample

Using a statistic to estimate a parameter as a single value is called estimation.

The theoretical sampling distribution of the mean.

A sample statistic may be used to estimate a.

In simple random sampling,.

If s=14 and N=49 , then ${ } ^ { s } \bar { X }$

The central limit theorem indicates that as sample size increases, the theoretical sampling distribution of the mean.

A population has a mean of 100 and a standard deviation of 15. If samples of size N = 25 are randomly drawn from this population, then what proportion of sample means will fall between 97 to 103?

The lower and upper scores of a confidence interval are called.

For population distributions that are not heavily skewed, many statisticians consider a minimum sample size of to produce a sampling distribution of the mean that will approximate a normal distribution.

In simple random sampling,.

If the sample mean has the same value as the population mean, then for that sample mean the.

The scores vary in the population and the the sample size, then the more accurately a sample mean will estimate a population mean.

In a sampling distribution of the mean, approximately percent of the sample means will be contained within the interval of two standard errors above and below the population mean.