What type of analysis would you use to determine the mean and standard deviation of a continuous data set?

Descriptive statistics is the appropriate analysis to use when determining the mean and standard deviation of a continuous data set because it focuses on summarizing and organizing the data. These statistics provide insights into the central tendency, variability, and distribution of the data without making predictions or inferences beyond the data itself.

For instance, the mean helps in understanding the average value of the dataset, while the standard deviation offers information about the spread or dispersion of the values around the mean. These measures are foundational in analyzing continuous data and are essential for any initial data analysis steps.

In contrast, qualitative analysis deals with non-numerical data and focuses on understanding characteristics, themes, and descriptions rather than quantifying variable measures. Inferential statistics, on the other hand, are used to make predictions or generalizations about a population based on sample data, going beyond mere description to assess relationships and differences. Causal-comparative analysis seeks to understand cause-and-effect relationships but does not directly provide descriptive measures such as the mean and standard deviation. Thus, descriptive statistics is specifically designed for summarizing and describing the inherent qualities of a dataset.