An interval estimate is a range of values within which the actual value of a population parameter falls.

Sure, I can explain the concept of interval estimate step by step.

1. An interval estimate is a statistical technique used to estimate the value of a population parameter.

2. A population parameter is a numerical value that describes a characteristic of a population, such as the mean or standard deviation.

3. Interval estimates are used because it is often impossible or impractical to measure an entire population, so we must rely on a sample of the population to make inferences about the population as a whole.

4. To create an interval estimate, we use a sample statistic, such as the sample mean or sample standard deviation, to estimate the population parameter.

5. The interval estimate is a range of values that we believe contains the true value of the population parameter.

6. The range is created by calculating a margin of error, which is based on the sample size and the level of confidence desired.

7. The level of confidence is the probability that the true population parameter falls within the interval estimate.

8. For example, if we create a 95% confidence interval for the population mean, we are saying that we are 95% confident that the true population mean falls within the range of values we have calculated.

9. Interval estimates are important because they allow us to make inferences about a population based on a sample, while acknowledging the uncertainty inherent in statistical analysis.