Medidas de Tendencia Central en Estadística
Comprender la media, mediana, moda y otras medidas de tendencia central
Interactive Measures of Central Tendency Visualization
Welcome to the Measures of Central Tendency Explorer
This interactive visualization helps you understand the three main measures of central tendency: mean, median, and mode. Explore how these measures behave differently with symmetric, skewed, and bimodal distributions.
What you can explore:
- Mean (x̄) - Average value, sensitive to outliers
- Median - Middle value, robust to outliers
- Mode - Most frequent value(s)
- Distribution Shapes - How measures relate to distribution shape
How to Use This Visualization
Interactive Features:
- • Select Distribution - Choose from different distribution types
- • Enter Custom Data - Input your own data values
- • Toggle Measures - Show/hide mean, median, and mode
- • Compare Values - See how measures differ
What You'll See:
- • Histogram - Frequency distribution of data
- • Mean Line (blue, dashed) - Average value
- • Median Line (purple, dashed) - Middle value
- • Mode Markers (orange) - Most frequent values
Measures of Central Tendency
Mean (x̄)
10.000
Σx / n = 170 / 17
Average of all values. Sensitive to outliers.
Median
10.000
Value at position 9
Middle value when sorted. Robust to outliers.
Mode
2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0
Frequency: 1
Most frequently occurring value(s).
Relationship Analysis
Mean ≈ Median: Approximately symmetric distribution
Mean - Median:
0.000
Mean - Mode:
8.000
Median - Mode:
8.000
Data Summary
Sample Size (n)
17
Minimum
2.00
Maximum
18.00
Range
16.00
Key Concepts
Mean: The arithmetic average. Sum all values and divide by count. Best for symmetric distributions without outliers.
Median: The middle value when data is sorted. For even n, average the two middle values. Best for skewed distributions or when outliers are present.
Mode: The most frequently occurring value(s). Can have multiple modes (bimodal, multimodal). Best for categorical or discrete data.
When to Use Each Measure
Use Mean: When data is symmetric, no outliers, and you need all values in calculation.
Use Median: When data is skewed, has outliers, or you need a robust measure.
Use Mode: For categorical data, finding most common category, or when you need the "typical" value.
Use All Three: Compare to understand distribution shape. Mean > Median indicates right skew, Mean < Median indicates left skew.
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