Measures of central tendency are statistical metrics that describe the center point or typical value of a dataset. The primary measures include mean (average), median (middle value), and mode (most frequent value).

Descriptive Statistics:This branch of statistics involves summarizing and organizing data to describe its main features. It includes calculating measures of central tendency (mean, median, mode) and measures of dispersion (range, variance, standard deviation). Descriptive statistics provide a comprehensive snapshot of the dataset's characteristics.

Forecasting:This involves making predictions about future data points based on historical data. While valuable for planning, it doesn't provide insights into the current dataset's central tendency.

Trend Analysis:This technique examines data over time to identify patterns or trends. It's useful for understanding data direction but doesn't focus on central tendency measures.

Gap Analysis:This method compares actual performance with potential or desired performance, identifying gaps between current and expected outcomes. It doesn't relate to measures of central tendency.

Therefore, to obtain basic measures of central tendency, an analyst should employ descriptive statistics.