Techniques that allow conclusions to be drawn about the relationships among different variables in a population sample are referred to as?

Inferential statistics are techniques that enable researchers to draw conclusions about relationships among different variables in a population based on the analysis of a sample. This involves using data from a representative sample to make inferences or generalizations about a larger population. The key aspect of inferential statistics is that it uses the concept of probability and sampling distributions to estimate population parameters and test hypotheses.

For instance, when researchers collect data from a smaller group and then apply inferential statistical methods, they can determine whether observed patterns or relationships are likely to be applicable to the broader population. This is particularly important in healthcare statistics, where researchers often have to make decisions based on limited data. By applying inferential techniques, they can assess risks, effectiveness of treatments, and other crucial metrics without needing data from the entire population.

In contrast, the other statistical approaches focus on different aspects. Descriptive statistics summarize or describe characteristics of a dataset without making predictions or inferences beyond the available data. Predictive statistics, on the other hand, specifically aim to forecast future outcomes based on existing data patterns. Explanatory statistics can serve to clarify or shed light on relationships within particular datasets but lack the broader inferential framework.

Overall, the capability of inferential statistics to extrapolate findings from a