A data analyst is creating a forecast for a product line introduced early last year. Which of the following should the analyst use to create projected sales and customer satisfaction for next year?

Standard deviation measures data dispersion, and constraints limit outcomes, but neither directly serve as primary attributes for creating projections themselves.

Mean and median are measures of central tendency used in descriptive statistics, but they are not the data types or attributes used for forecasting.

Boolean data represents true/false values, and arrays are data structures, neither of which are the primary attribute types for sales and satisfaction forecasting.

Numerical attributes (like sales figures) are essential for quantitative forecasting, while ordinal attributes (like customer satisfaction ratings, e.g., on a scale of 1-5) provide ranked data that can also be analyzed to project future trends. Both are crucial for comprehensive forecasting.