Calculate mean, median, mode, standard deviation, variance, quartiles, and more. Complete statistical analysis with visualizations.
Mean
27.0000
n = 10
Mean
27.0000
n = 10
Quick-start with common scenarios
Test your skills with practice problems
Practice with 4 problems to test your understanding.
Mean
27.0000
Median
26.5000
Mode
12, 15, 18...
Geometric Mean
24.9720
Std Deviation
10.7806
Variance
116.2222
Range
33.0000
CV
39.93%
Standard Error
3.4091
Sum
270
Min
12
Q1 (25%)
19.00
Q2 (Median)
26.50
Q3 (75%)
33.75
Max
45
Interquartile Range (IQR)
IQR = Q3 - Q1 = 33.75 - 19.00 = 14.75
Skewness
0.2887
Approximately symmetric
Kurtosis (Excess)
-0.8447
Platykurtic (light tails)
12, 15, 18, 22, 25, 28, 30, 35, 40, 45
Mean
x̄ = Σx / n
Variance (sample)
s² = Σ(x - x̄)² / (n-1)
Standard Deviation
s = √(variance)
Standard Error
SE = s / √n
For a data set, calculate: Mean (average) = sum of values / count. Median = middle value when sorted. Mode = most frequent value. Standard deviation measures spread from mean. Variance = standard deviation squared. For data [2,4,4,4,5,5,7,9]: Mean = 5, Median = 4.5, Mode = 4, Standard Deviation = 2.14, Variance = 4.57.
A statistics calculator performs comprehensive statistical analysis including measures of central tendency (mean, median, mode), measures of spread (variance, standard deviation, range), and data distribution analysis.
For a data set, calculate: Mean (average) = sum of values / count. Median = middle value when sorted. Mode = most frequent value. Standard deviation measures spread from mean. Variance = standard deviation squared. For data [2,4,4,4,5,5,7,9]: Mean = 5, Median = 4.5, Mode = 4, Standard Deviation = 2.14, Variance = 4.57.
Mean is the average (sum/count). Median is the middle value when sorted. Mode is the most frequent value. Use mean for symmetric data, median for skewed data (resistant to outliers), and mode for categorical data.
Standard deviation measures how spread out data is from the mean. Low SD means data clusters near the mean; high SD means data is spread out. It's the square root of variance and uses the same units as the original data.
Quartiles divide sorted data into four equal parts. Q1 (25th percentile), Q2 (median), Q3 (75th percentile). IQR (Interquartile Range) = Q3 - Q1, representing the middle 50% of data. Used to identify outliers.
Skewness measures asymmetry: positive = right tail longer, negative = left tail longer, zero = symmetric. Kurtosis measures tail heaviness: positive = heavy tails, negative = light tails. Normal distribution has skewness 0, kurtosis 0.
Coefficient of Variation (CV) is the standard deviation expressed as a percentage of the mean: CV = (SD/mean) × 100%. It allows comparison of variability between datasets with different units or vastly different means.
Last updated: 2025-01-15
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Mean
27.0000
n = 10