Final answer:
Inferential statistics are used by researchers to determine if a study's findings can be generalized to a larger population, with the null hypothesis being rejected if the results are statistically significant. A meta-analysis can be employed if numerous studies have been conducted to estimate the effect size across a population.
Step-by-step explanation:
Researchers use inferential statistics in order to see if a finding is applicable to a large population. If the data are statistically significant, researchers can reject the null hypothesis, or the assumption that there is no relationship between the variables. If many studies are done, researchers can use a meta-analysis to estimate the effect size for a total population.
In the process of hypothesis testing, researchers collect data from a sample and evaluate it to determine if there is sufficient evidence to reject the null hypothesis. This involves using statistical analysis to decide whether any observed differences are due to chance or if they reflect an actual relationship or effect. The goal is to ascertain the reliability and generalizability of the research findings to the larger population.