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Find the mode (most frequent value) of a dataset. Handles multimodal data and shows frequency analysis.
The mode is the value that appears most frequently in a dataset. Unlike mean and median, mode can be used for categorical data and there can be multiple modes or no mode at all.
One clear peak. Common in normal distributions (test scores, heights).
Two peaks. Often indicates two distinct groups (male/female heights).
Multiple peaks. Suggests several distinct groups or patterns.
Sizes: 7, 8, 8, 9, 9, 9, 9, 10, 10, 11
Mode = 9 (appears 4 times)
Most common size - helps with inventory decisions
Ages: 25, 25, 25, 32, 45, 45, 45, 52, 60
Modes = 25, 45 (bimodal)
Two distinct customer groups for targeted marketing
Colors, brands, categories (most popular shirt color)
Most common shoe size, most frequent error code
Multiple modes can reveal distinct groups in data
Yes! If all values appear with equal frequency (or each value appears only once), there is no mode. For example: 1, 2, 3, 4, 5 has no mode since each appears once.
Mode is the most frequent value, mean is the average (sum ÷ count), and median is the middle value when sorted. Mode is best for categorical data, median for skewed data, and mean for symmetric data.
Yes! A dataset can be multimodal with 3, 4, or more modes. For example: 1, 1, 2, 2, 3, 3 has three modes (1, 2, and 3).
Yes, the mode must be an actual value from your dataset. It's the value that appears most frequently, so it has to exist in the data.
Mode helps identify the most common choices: most popular product size, most frequent customer complaint, peak shopping hour. This guides inventory, staffing, and product development decisions.
Yes, but it's less useful with continuous data since exact repeats are rare. For example, heights like 170.1, 170.2, 170.1 cm would have mode 170.1, but if all heights are unique, there's no mode.