Final answer:
The correct answer is option c) quantitative data.The most preferred average for quantitative data is the mean, which sums all numeric values and divides by the count, making it most informative for datasets without significant outliers.
Step-by-step explanation:
The mean, also known as the arithmetic average, is particularly useful when dealing with quantitative data. It measures the central tendency by summing all values and dividing by their count. Although the mean can be calculated for different types of data, it is most informative for quantitative data because quantitative values can be meaningfully averaged. For grouped data or frequency distributions, a mean can be estimated, but it may not be as accurate due to the lack of individual data points. When dealing with outliers or extreme values, other measures of central tendency such as the median may be preferred.
Even though the mean can be used for other types of data, its sensitivity to extreme values (i.e., outliers) can distort the representation of the central tendency. Because of this, in cases where the data is heavily skewed or contains outliers, the median is often a better measure of central tendency than the mean. Still, for most quantitative datasets with a normal distribution, the mean serves as the most preferred measure of central tendency.