What is meant by "sample size" in data collection?

The term "sample size" refers specifically to the number of observations or data points chosen for analysis from a larger population. It is a crucial aspect of data collection because the sample size can significantly influence the reliability and validity of the results obtained from a study. A well-chosen sample size helps ensure that the findings are representative of the larger population, thereby allowing for better generalization of results.

In data collection, selecting an appropriate sample size is essential for reducing sampling error and ensuring statistical power. If the sample size is too small, it may not capture the overall characteristics of the population, leading to inaccurate conclusions. Conversely, a sufficiently large sample size often enhances the accuracy and credibility of the analytical outcomes.

The other options do not accurately define "sample size." The total number of variables in a study refers to the different attributes or characteristics measured, not the number of observations. The average value of a population pertains to central tendency and does not imply anything about sample size. Lastly, the range of data collected indicates the spread between the highest and lowest values but does not convey how many data points were included in the sample.