A research method that focuses on collecting and analyzing numerical data to identify patterns, relationships, and trends, often using surveys or experiments. Essential for making data-driven decisions and validating hypotheses with statistical evidence.
A type of data visualization that uses dots to represent values for two different numeric variables, plotted along two axes. Essential for identifying relationships, patterns, and outliers in datasets used in digital product design and analysis.
The interpretation of historical data to identify trends and patterns. Important for understanding past performance and informing future decision-making.
Newly developing patterns or shifts in technology, behavior, or design that have the potential to influence future practices and strategies. Important for staying ahead of the curve and adapting to changes in the industry.
A phenomenon where learning is improved when study sessions are spaced out over time rather than crammed together. Crucial for designing educational and training programs that enhance long-term retention.