Statistics Калькулятор
Вычислить various statistical metrics like mean, median, mode, variance, and standard deviation from a list of numbers.
Separate numbers with commas, spaces, or line breaks
Central Tendency
Mean
9.6522
The average value
Median
9
The middle value
Mode
5
Most frequent value(s)
Dispersion
Range
19
Max - Min
Variance
33.9660
Spread from the average
Standard Deviation
5.8280
Data concentration
Interquartile Range (IQR)
9.5000
Middle 50% spread
Shape of Distribution
Skewness
0.2315
Asymmetry of distribution
Kurtosis
-1.2321
Tailedness of distribution
Other Statistics
Minimum
1
Maximum
20
Sum
222
Count
23
Percentiles
25th Percentile
5
First Quartile
50th Percentile
9
Median
75th Percentile
14.5000
Third Quartile
About the Statistics Калькулятор
Understanding Central Tendency
Mean (Average)
The mean is the sum of all numbers divided by the count of numbers. It's the most common measure of the center of a dataset.
Median
The median is the middle value in a sorted list of numbers. It's less affected by outliers than the mean.
Mode
The mode is the number that appears most frequently in a list. A dataset can have one mode, more than one mode, or no mode.
Understanding Dispersion
Range
The range is the difference between the highest and lowest values, giving a simple measure of spread.
Variance
Variance measures how far each number in the set is from the mean. A high variance indicates that the numbers are very spread out.
Standard Deviation
This is the square root of the variance. It's a widely used measure of the amount of variation or dispersion.
Interquartile Range (IQR)
The IQR is the range of the middle 50% of the data. It's calculated as the difference between the 75th and 25th percentiles and is robust against outliers.
Understanding the Shape of Distribution
Skewness
Skewness describes the asymmetry of the data. A value of 0 indicates a symmetrical distribution. A positive value means a tail to the right, and a negative value means a tail to the left.
Kurtosis
Kurtosis is a measure of the 'tailedness' of the distribution. High kurtosis means more of the variance is due to infrequent extreme deviations, as opposed to frequent modest deviations.