INTERVAL ESTIMATE

Interval estimates are a type of statistical analysis used to measure the reliability of results from a sample population. They provide an estimated range of values that a population parameter is likely to fall within, based on data gathered from a sample. Interval estimates are commonly used in survey research to determine the precision of population estimates. This article provides an overview of interval estimates and their applications in survey research.

Interval estimates are based on the idea that a population parameter can be estimated from a sample of data. The population parameter is the true value of the population, whereas the sample parameter is the estimated value from the sample. The interval estimate is the range of values that the population parameter is likely to fall within. This range is determined by the confidence level of the estimate, which is typically set at 95%.

Interval estimates can be calculated using a variety of methods, including the student’s t-test, the z-test, and the chi-square test. Each of these methods assumes that the sample is randomly drawn from the population and that the sample size is sufficiently large enough to be representative. To calculate an interval estimate, the sample mean and standard deviation of the sample are calculated. The confidence level is then used to calculate the margin of error, which is a measure of the precision of the interval estimate.

Interval estimates are commonly used in survey research to measure the accuracy of population estimates. For example, a survey may be conducted to estimate the percentage of people in a given area who support a particular political candidate. An interval estimate can be used to determine the precision of this estimate. The confidence level of the estimate can be adjusted to account for the number of people surveyed, the population size, and the sample size.

Interval estimates can also be used to measure the reliability of results from experiments. For example, an experiment may be conducted to determine the effectiveness of a new drug. An interval estimate can be used to determine the precision of the results and to assess the likelihood that the true effect of the drug falls within the range of the interval estimate.

In summary, interval estimates are a type of statistical analysis used to measure the reliability of results from a sample population. They provide an estimated range of values that a population parameter is likely to fall within, based on data gathered from a sample. Interval estimates are commonly used in survey research to determine the precision of population estimates and in experiments to measure the reliability of results.

References

Aguinis, H., Gottfredson, R. K., & Joo, H. (2012). Introduction to Statistics in Psychology. Pearson Education.

Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Routledge.

Thompson, B. (2001). Sampling. Sage.