Confidence Intervals and Estimation

A single value derived from sample data to estimate a population parameter

A method to calculate the standard deviation

The true mean of a population

A range of values used to estimate a population parameter

Sample mean

Interval estimate

Point estimate

Confidence level

Lower Confidence Level and Upper Confidence Level

Lower Confidence Limit and Upper Confidence Limit

Lower Calculation Level and Upper Calculation Level

Lower Calculation Limit and Upper Calculation Limit

It is subtracted from and added to the sample mean

It is multiplied by the sample mean

It is used to find the standard deviation

It is divided by the sample mean

95% of the data falls within the confidence interval

95% of the time, the sample mean equals the population mean

95% of the confidence intervals will contain the true population parameter

There is a 95% chance that the sample mean is correct

99%

95%

85%

90%

The interval is 90% of the sample mean

The interval is 90% accurate

90% of the intervals will contain the true population mean

The sample mean is 90% of the population mean

There is a 95% chance the population mean is between 21.5 and 24.5

95% of the time, the population mean is exactly 23

The population mean is always between 21.5 and 24.5

We are 95% confident that the interval from 21.5 to 24.5 contains the true population mean

It implies probability about a fixed parameter

It suggests the interval is always correct

It assumes the sample mean is the population mean

It indicates the interval is too wide

The only interval that contains the population mean

One of many possible intervals that might contain the population mean

The average of all possible intervals

The exact population mean