Large Sample Methods
- Techniques for drawing population inferences from samples when the number of observations is large.
- Two primary approaches: hypothesis testing (testing claims about populations) and estimation (estimating population parameters).
- Helpful for more precise inferences and for identifying or controlling potential sources of bias and error in large or complex data sets.
Definition
Section titled “Definition”Large sample methods are statistical techniques used to analyze data sets with a large number of observations. These methods are useful for making inferences about a population based on the characteristics of a sample. There are two main types of large sample methods: hypothesis testing and estimation.
Explanation
Section titled “Explanation”- Hypothesis testing is a statistical procedure that involves testing a specific claim or assumption about a population. It is used to determine whether a statistical relationship exists between two variables in a sample by evaluating the likelihood of the null hypothesis relative to an alternative hypothesis.
- Estimation is a statistical procedure that uses sample data to make inferences about population characteristics, such as a population mean or median, by calculating a corresponding sample statistic and using it as an estimate for the population parameter.
- Large sample methods enable researchers to draw conclusions from substantial amounts of data, which can improve the accuracy and precision of inferences and assist in identifying and controlling potential sources of bias and error.
Examples
Section titled “Examples”Hypothesis testing example
Section titled “Hypothesis testing example”A researcher might use hypothesis testing to determine whether there is a significant difference in the average income of men and women in a particular population. In this case, the null hypothesis would be that there is no difference in average income between men and women, and the alternative hypothesis would be that there is a difference. The researcher would then use statistical tests to determine the likelihood of the null hypothesis being true.
Estimation example
Section titled “Estimation example”A researcher might use estimation to determine the average height of adults in a particular population. The researcher would collect a sample of adults and measure their heights. The researcher would then use statistical techniques to calculate the average height of the sample, and use this value to estimate the average height of the population.
Use cases
Section titled “Use cases”- Making inferences about a population from a large sample.
- Working with large and complex data sets where more precise and accurate estimates are needed.
- Identifying and controlling potential sources of bias and error to improve validity and reliability of findings.
Related terms
Section titled “Related terms”- Hypothesis testing
- Estimation