What statistical method is used to analyze data collected from a sample?

Inferential statistics is the appropriate method used to analyze data collected from a sample. This branch of statistics allows researchers to draw conclusions and make predictions about a population based on the data obtained from a sample. The core function of inferential statistics is to allow generalizations beyond the immediate data, meaning that it helps in estimating population parameters, testing hypotheses, and making forecasts.

When using inferential statistics, techniques such as confidence intervals and significance tests are utilized to infer trends and characteristics of the larger population. This is crucial because collecting data from an entire population can often be impractical or impossible, making samples the practical choice for analysis.

In contrast, descriptive statistics primarily summarize and describe the features of a dataset rather than infer broader conclusions. Qualitative analysis focuses on non-numerical data, concentrating on understanding concepts, thoughts, or experiences rather than statistical relationships. Quantitative analysis typically involves the examination of numerical data but does not necessarily involve the inference process that characterizes inferential statistics. Thus, the key aspect of inferential statistics is its capability to extend findings from a sample to a larger population.