What is the primary objective of inferential statistics?

The primary objective of inferential statistics is to draw conclusions and make predictions about a population based on a sample of data. Inferential statistics allows researchers to take a smaller subset of data and extrapolate findings to a larger group, enabling them to answer broader questions without needing to collect data from every individual in that population. This process often involves hypothesis testing, confidence intervals, and making predictions, all of which are fundamental to forming insights about the population being studied.

The other options address different aspects of statistical analysis. Summarizing sample data is a role of descriptive statistics rather than inferential statistics. Measures of central tendency, such as mean or median, are descriptive statistics that provide a snapshot of the sample data without making broader population inferences. Determining data validity pertains more to the quality and accuracy of data collection and measurement rather than the inferential processes that use that data to inform about a population.