Sampling Distributions

The distribution of the entire population.

The distribution of possible values for the population mean.

The distribution of individual data points in the sample.

The distribution of possible values for the sample mean if the study were repeated many times.

The population distribution of test scores is uniform.

The scores are independent and identically distributed.

Each student's score must be at least 73 or no more than five points below the mean.

The scores come from a normal distribution with mean 78.

Limited estimates range.

Increased bias.

Improved precision.

Increased randomness.

The population mean ($\mu$)

The median of the population

The mode of the population

The sample standard deviation ($s$)

Using a small sample size.

Using a large sample size.

Selection bias favoring less financially successful business owners.

Selection bias favoring financially successful business owners.

Sampling variability.

Parameter stability.

Inferential accuracy.

Statistical bias.

Mean

Range

Sample deviation

Standard error (SE)

It becomes more normal or bell-shaped

It becomes skewed right

Its shape remains unchanged regardless of sample size

It becomes skewed left

The sample size required for maintaining the same margin of error

The z* value used in calculating the interval

The width of the confidence interval

The probability that the interval does not contain the true population mean

Increase the sample size to achieve a lower margin of error because this narrows down the confidence interval.

Collect data from a convenience sampling method, assuming it will be representative enough to decrease margin of error.

Use a stratified random sample instead of a simple random sample to improve precision.

Decrease the sample size to reduce costs, and therefore margin of error by association.