Inferential statistics is a data analysis technique used in quantitative research to make inferences or draw conclusions about a population based on a sample. It involves using statistical methods to analyze the data collected from a sample and then generalize the findings to the larger population from which the sample was drawn.

The main goal of inferential statistics is to make predictions, test hypotheses, or estimate parameters of the population using the sample data. It helps researchers determine if the findings from the sample are statistically significant and can be applied to the population as a whole.

Some common inferential statistical techniques include hypothesis testing, confidence intervals, and regression analysis. These techniques allow researchers to determine the likelihood of an observed effect being due to chance, estimate the range within which a population parameter is likely to fall, and examine the relationships between variables, respectively.

Overall, inferential statistics plays a crucial role in quantitative research by allowing researchers to make meaningful inferences and draw conclusions about populations based on limited sample data.