What is the aim of inferential statistics?

The aim of inferential statistics is to make predictions about a population based on sample data. This branch of statistics involves using the information gathered from a sample— a subset of the population—to draw conclusions about the larger group. By applying various statistical techniques, it allows researchers to estimate population parameters, test hypotheses, and make generalizations with a degree of certainty, often quantified via confidence intervals and p-values.

In contrast, summarizing data in a clear form relates more to descriptive statistics, which focuses on presenting and organizing data but does not extend to making predictions or inferences. Measuring data variability, which involves understanding how spread out or clustered the data points are, is another descriptive statistic function that does not predict anything about a population. Assessing the accuracy of data collection methods is related to research validity and reliability but does not describe the inferential process of predicting outcomes based on sample data. Therefore, the correct choice reflects the core purpose of inferential statistics.