Calculadora de média, mediana e moda

Mean, median, and mode are the three most common ways to describe the "center" of a dataset. The mean is the sum of all values divided by how many there are. The median is the middle value once the data is sorted (or the average of the two middle values for an even-sized list). The mode is the value (or values) that appear most often — a dataset can have no mode, one mode, or several.

Mean is sensitive to outliers — a single very large or small value can pull it far from most of the data. Median is more robust in that case, which is why median household income, for example, is reported instead of the mean. Mode is most useful for categorical or repeating data.

Example: for the dataset 2, 4, 4, 4, 5, 5, 7, 9, the mean is 5, the median is 4.5 (the average of the two middle values, 4 and 5), and the mode is 4 (it appears three times, more than any other value).

For skewed income or home-price data, the median often describes a typical household better than the mean because a few extreme values pull the average up.

Mode is the only measure that works cleanly on categorical labels (favorite color, shoe size) when those labels are coded as numbers.

Worked example with default list 2, 4, 4, 4, 5, 5, 7, 9: mean = 5, median = 4.5, mode = 4 (appears three times).

Bimodal datasets (two peaks) report multiple modes — test scores clustered at B and A grades may show modes at both letter-grade boundaries when numeric midpoints are used. Bimodal tests may show two modes when clusters sit at B and A numeric midpoints — report all modes the dataset returns. Report every mode the tool finds when a bimodal grade distribution has two distinct peaks.

Weighted mean differs from this unweighted tool — GPA with 4-credit versus 1-credit courses needs Σ(weight×value)/Σ(weights), not a simple comma-separated list average. Weighted GPA needs Σ(weight×value)/Σ(weights) — four-credit labs outweigh one-credit seminars unlike this comma-list unweighted average. Label this output as unweighted when your syllabus expects credit-weighted GPA calculations.

Trimmed mean (drop top/bottom 10%) reduces outlier impact without switching fully to median — stock analysts use trimmed means when a few extreme days skew simple average returns. Trimmed mean dropping top/bottom ten percent softens outlier impact — analysts use it when a few extreme market days skew simple returns. Mention trimmed-mean alternatives when one outlier would distort the simple mean you report.