Uncommons Maths API
(Version 1.2.3)

org.uncommons.maths.statistics Class DataSet

```java.lang.Object
org.uncommons.maths.statistics.DataSet
```

`public class DataSetextends Object`

Utility class for calculating statistics for a finite data set.

Author:
Daniel Dyer
How To Analyze Data Using the Average

Constructor Summary
`DataSet()`
Creates an empty data set with a default initial capacity.
`DataSet(double[] dataSet)`
Creates a data set and populates it with the specified values.
`DataSet(int capacity)`
Creates an empty data set with the specified initial capacity.

Method Summary
` void` `addValue(double value)`
Adds a single value to the data set and updates any statistics that are calculated cumulatively.
` double` `getAggregate()`

` double` `getArithmeticMean()`
The arithemthic mean of an n-element set is the sum of all the elements divided by n.
` double` `getGeometricMean()`
The geometric mean of an n-element set is the nth-root of the product of all the elements.
` double` `getHarmonicMean()`
The harmonic mean of an n-element set is n divided by the sum of the reciprocals of the values (where the reciprocal of a value x is 1/x).
` double` `getMaximum()`

` double` `getMeanDeviation()`
Calculates the mean absolute deviation of the data set.
` double` `getMedian()`
Determines the median value of the data set.
` double` `getMinimum()`

` double` `getProduct()`

` double` `getSampleStandardDeviation()`
The sample standard deviation is the square root of the sample variance.
` double` `getSampleVariance()`
Calculates the variance (a measure of statistical dispersion) of the data set.
` int` `getSize()`
Returns the number of values in this data set.
` double` `getStandardDeviation()`
The standard deviation is the square root of the variance.
` double` `getVariance()`
Calculates the variance (a measure of statistical dispersion) of the data set.

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

DataSet

`public DataSet()`
Creates an empty data set with a default initial capacity.

DataSet

`public DataSet(int capacity)`
Creates an empty data set with the specified initial capacity.

Parameters:
`capacity` - The initial capacity for the data set (this number of values will be able to be added without needing to resize the internal data storage).

DataSet

`public DataSet(double[] dataSet)`
Creates a data set and populates it with the specified values.

Parameters:
`dataSet` - The values to add to this data set.
Method Detail

`public void addValue(double value)`
Adds a single value to the data set and updates any statistics that are calculated cumulatively.

Parameters:
`value` - The value to add.

getSize

`public final int getSize()`
Returns the number of values in this data set.

Returns:
The size of the data set.

getMinimum

`public final double getMinimum()`
Returns:
The smallest value in the data set.
Throws:
`EmptyDataSetException` - If the data set is empty.
Since:
1.0.1

getMaximum

`public final double getMaximum()`
Returns:
The biggest value in the data set.
Throws:
`EmptyDataSetException` - If the data set is empty.
Since:
1.0.1

getMedian

`public final double getMedian()`
Determines the median value of the data set.

Returns:
If the number of elements is odd, returns the middle element. If the number of elements is even, returns the midpoint of the two middle elements.
Since:
1.0.1

getAggregate

`public final double getAggregate()`
Returns:
The sum of all values.
Throws:
`EmptyDataSetException` - If the data set is empty.

getProduct

`public final double getProduct()`
Returns:
The product of all values.
Throws:
`EmptyDataSetException` - If the data set is empty.

getArithmeticMean

`public final double getArithmeticMean()`
The arithemthic mean of an n-element set is the sum of all the elements divided by n. The arithmetic mean is often referred to simply as the "mean" or "average" of a data set.

Returns:
The arithmetic mean of all elements in the data set.
Throws:
`EmptyDataSetException` - If the data set is empty.
`getGeometricMean()`

getGeometricMean

`public final double getGeometricMean()`
The geometric mean of an n-element set is the nth-root of the product of all the elements. The geometric mean is used for finding the average factor (e.g. an average interest rate).

Returns:
The geometric mean of all elements in the data set.
Throws:
`EmptyDataSetException` - If the data set is empty.
`getArithmeticMean()`, `getHarmonicMean()`

getHarmonicMean

`public final double getHarmonicMean()`
The harmonic mean of an n-element set is n divided by the sum of the reciprocals of the values (where the reciprocal of a value x is 1/x). The harmonic mean is used to calculate an average rate (e.g. an average speed).

Returns:
The harmonic mean of all the elements in the data set.
Throws:
`EmptyDataSetException` - If the data set is empty.
Since:
1.1
`getArithmeticMean()`, `getGeometricMean()`

getMeanDeviation

`public final double getMeanDeviation()`
Calculates the mean absolute deviation of the data set. This is the average (absolute) amount that a single value deviates from the arithmetic mean.

Returns:
The mean absolute deviation of the data set.
Throws:
`EmptyDataSetException` - If the data set is empty.
`getArithmeticMean()`, `getVariance()`, `getStandardDeviation()`

getVariance

`public final double getVariance()`
Calculates the variance (a measure of statistical dispersion) of the data set. There are different measures of variance depending on whether the data set is itself a finite population or is a sample from some larger population. For large data sets the difference is negligible. This method calculates the population variance.

Returns:
The population variance of the data set.
Throws:
`EmptyDataSetException` - If the data set is empty.
`getSampleVariance()`, `getStandardDeviation()`, `getMeanDeviation()`

getStandardDeviation

`public final double getStandardDeviation()`
The standard deviation is the square root of the variance. This method calculates the population standard deviation as opposed to the sample standard deviation. For large data sets the difference is negligible.

Returns:
The standard deviation of the population.
Throws:
`EmptyDataSetException` - If the data set is empty.
`getSampleStandardDeviation()`, `getVariance()`, `getMeanDeviation()`

getSampleVariance

`public final double getSampleVariance()`
Calculates the variance (a measure of statistical dispersion) of the data set. There are different measures of variance depending on whether the data set is itself a finite population or is a sample from some larger population. For large data sets the difference is negligible. This method calculates the sample variance.

Returns:
The sample variance of the data set.
Throws:
`EmptyDataSetException` - If the data set is empty.
`getVariance()`, `getSampleStandardDeviation()`, `getMeanDeviation()`

getSampleStandardDeviation

`public final double getSampleStandardDeviation()`
The sample standard deviation is the square root of the sample variance. For large data sets the difference between sample standard deviation and population standard deviation is negligible.

Returns:
The sample standard deviation of the data set.
Throws:
`EmptyDataSetException` - If the data set is empty.
`getStandardDeviation()`, `getSampleVariance()`, `getMeanDeviation()`