Merge pull request #20 from cicirello/feature-stdev

Added methods for sample standard deviation

CHANGELOG.md

@@ -4,7 +4,7 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
-## [Unreleased] - 2021-12-22
+## [Unreleased] - 2022-02-11
 
 ### Added
 
@@ -17,11 +17,19 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Fixed
 
 ### CI/CD
-* Added automated commenting of test coverage percentages to CI/CD workflow.
 
 ### Other
 
 
+## [1.2.0] - 2022-02-11
+
+### Added
+* Statistics.stdev(int[]) and Statistics.stdev(double[]) methods for sample standard deviation.
+
+### CI/CD
+* Added automated commenting of test coverage percentages to CI/CD workflow.
+
+
 ## [1.1.0] - 2021-9-22
 
 ### Added

src/main/java/org/cicirello/math/stats/Statistics.java

@@ -41,7 +41,7 @@ private Statistics() {}
 	public static double mean(int[] data) {
 		int sum = 0;
 		for (int e : data) sum = sum + e;
-		return 1.0 * sum / data.length;
+		return ((double)sum) / data.length;
 	}
 
 	/**
@@ -126,6 +126,24 @@ public static double varianceSample(double[] data) {
 		return (sumSquares - sum*sum/data.length)/(data.length-1.0);
 	}
 
+	/**
+	 * Computes the sample standard deviation.
+	 * @param data The dataset.
+	 * @return the sample standard deviation.
+	 */
+	public static double stdev(int[] data) {
+		return Math.sqrt(varianceSample(data));
+	}
+
+	/**
+	 * Computes the sample standard deviation.
+	 * @param data The dataset.
+	 * @return the sample standard deviation.
+	 */
+	public static double stdev(double[] data) {
+		return Math.sqrt(varianceSample(data));
+	}
+
 	/**
 	 * Computes covariance for a pair of random variables.
 	 * @param X Array of samples of first variable.

src/test/java/org/cicirello/math/stats/StatisticsTests.java

@@ -146,6 +146,44 @@ public void testSampleVarianceOfDoubles() {
 		}	
 	}
 
+	@Test
+	public void testStdevOfInts() {
+		for (int n = 1; n <= 10; n++) {
+			int[] data = new int[n];
+			for (int i = 0; i < n; i++) {
+				data[i] = 3;
+			}
+			assertEquals("All elements the same", 0.0, Statistics.stdev(data), EPSILON);
+		}
+		// Note: This assumes that the variance method passes its tests.
+		for (int n = 2; n <= 10; n++) {
+			int[] data = new int[n];
+			for (int i = 0; i < n; i++) {
+				data[i] = i+1;
+			}
+			assertEquals("ints from 1 to n", Math.sqrt(Statistics.variance(data)*n/(n-1)), Statistics.stdev(data), EPSILON);
+		}	
+	}
+
+	@Test
+	public void testStdevOfDoubles() {
+		for (int n = 1; n <= 10; n++) {
+			double[] data = new double[n];
+			for (int i = 0; i < n; i++) {
+				data[i] = 3;
+			}
+			assertEquals("All elements the same", 0.0, Statistics.stdev(data), EPSILON);
+		}
+		// Note: This assumes that the variance method passes its tests.
+		for (int n = 2; n <= 10; n++) {
+			double[] data = new double[n];
+			for (int i = 0; i < n; i++) {
+				data[i] = i+1;
+			}
+			assertEquals("ints from 1 to n", Math.sqrt(Statistics.variance(data)*n/(n-1)), Statistics.stdev(data), EPSILON);
+		}	
+	}
+
 	@Test
 	public void testCovarianceOfInts() {
 		for (int n = 1; n <= 10; n++) {