IBM Data Science Practice Test

What benefit does the use of inferential statistics provide?

1. Helps in measuring central tendency.

2. Allows conclusions from a sample to the entire population.

3. Only describes data without making any conclusions.

4. Focuses on sampling error.

The correct answer is: Allows conclusions from a sample to the entire population.

The use of inferential statistics is crucial because it allows researchers to draw conclusions or make inferences about a larger population based on the analysis of a sample. This method relies on probability theory and helps in estimating population parameters, testing hypotheses, and making predictions. By using sample data, inferential statistics enables one to generalize findings beyond the sample itself, which is particularly important when it is impractical or impossible to collect data from the entire population. This capability is vital in fields like social sciences, medicine, and market research, where understanding the broader implications of sample observations can lead to significant insights. While measuring central tendency (mean, median, mode) and focusing on sampling error are important aspects of statistical analysis, they do not capture the essence of what inferential statistics provides, which is a bridge from sample-specific findings to broader population conclusions. Descriptive statistics, on the other hand, simply summarizes the sample data without making broader generalizations.