Basic statistics implementation, not yet integrated.

src/main/java/com/whichclasses/statistics/ConcreteAggregator.java

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+package com.whichclasses.statistics;
+
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.Collections;
+import java.util.List;
+import java.util.Map;
+
+import com.google.common.collect.Maps;
+import com.google.inject.Inject;
+import com.whichclasses.model.Course;
+import com.whichclasses.model.DataSource;
+import com.whichclasses.model.Department;
+import com.whichclasses.model.proto.TceRating.Question;
+
+public class ConcreteAggregator implements DataAggregator {
+
+  DataSource dataSource;
+  Map<String, Map<Question, Double>> courseScoreDataMap = Maps.newHashMap();
+
+  @Inject
+  public ConcreteAggregator(DataSource dataSource) {
+    this.dataSource = dataSource;
+  }
+
+  @Override
+  public List<Course> getRankedCourses(String deptId, Question question) {
+    Department dept = dataSource.getDepartmentList().getChildren().get(deptId);
+    Collection<Course> courses = dept.getChildren().values();
+    List<Course> courseList = new ArrayList<Course>(courses);
+    Collections.sort(courseList, new SimpleCourseComparator(question));
+    return courseList;
+  }
+
+}

src/main/java/com/whichclasses/statistics/DataAggregator.java

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+package com.whichclasses.statistics;
+
+import java.util.List;
+
+import com.whichclasses.model.Course;
+import com.whichclasses.model.proto.TceRating.Question;
+
+public interface DataAggregator {
+  public List<Course> getRankedCourses(String deptId, Question question);
+}

src/main/java/com/whichclasses/statistics/Rateable.java

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+package com.whichclasses.statistics;
+
+import com.whichclasses.model.proto.TceRating;
+
+public interface Rateable {
+  public int getRatingCount(TceRating.Question question);
+  public double getAverageScore(TceRating.Question question);
+  public double getWilsonScore(TceRating.Question question);
+}

src/main/java/com/whichclasses/statistics/RateableCollection.java

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+package com.whichclasses.statistics;
+
+import java.util.Collection;
+import java.util.Map;
+
+import com.google.common.collect.Maps;
+import com.whichclasses.model.proto.TceRating;
+import com.whichclasses.model.proto.TceRating.Question;
+
+public class RateableCollection implements Rateable {
+
+  private Collection<? extends Rateable> children;
+  private Map<Question, Double> questionToScore = Maps.newHashMap();
+  private Map<Question, Double> questionToWilsonScore = Maps.newHashMap();
+  private Map<Question, Integer> questionToNumRatings = Maps.newHashMap();
+
+  public RateableCollection( Collection<? extends Rateable> children ) {
+    this.children = children;
+    calculateStatistics();
+  }
+
+  private void calculateStatistics() {
+    for(Question question : Question.values()) {
+      double qualityPoints = 0;
+      int numRatings = 0;
+      for(Rateable rateable : children) {
+        qualityPoints += rateable.getAverageScore(question) * rateable.getRatingCount(question);
+        numRatings += rateable.getRatingCount(question);
+      }
+      double averageScore = numRatings != 0 ? qualityPoints / numRatings : 0;
+      double wilsonScore = calculateWilsonScore((averageScore - 1) / 4, numRatings) * 4 + 1;
+      questionToScore.put(question, averageScore);
+      questionToWilsonScore.put(question, wilsonScore);
+      questionToNumRatings.put(question, numRatings);
+    }
+  }
+
+  @Override
+  public double getAverageScore(TceRating.Question question) {
+    return questionToScore.get(question);
+  }
+
+  @Override
+  public int getRatingCount(TceRating.Question question) {
+    return questionToNumRatings.get(question);
+  }
+
+  @Override
+  public double getWilsonScore(TceRating.Question question) {
+    return questionToWilsonScore.get(question);
+  }
+
+  /**
+   * Calculates the lower bound of the 95% confidence interval of a normalized data set of data
+   * @param p - Normalized average of sample data set
+   * @param n - Number of samples
+   * @return The normalized Wilson score of a normalized data set
+   */
+  private double calculateWilsonScore(double p, int n) {
+    if(n == 0) return 0;
+    double z = 1.96;
+    return (p + z*z/(2*n) - z*Math.sqrt(p*(1-p)/n + z*z/(4*n*n)))/(1 + z*z/n);
+  }
+
+}

src/main/java/com/whichclasses/statistics/SimpleCourseComparator.java

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+package com.whichclasses.statistics;
+
+import java.util.Comparator;
+
+import com.whichclasses.model.Course;
+import com.whichclasses.model.proto.TceRating.Question;
+
+public class SimpleCourseComparator implements Comparator<Course> {
+
+  private Question question;
+
+  public SimpleCourseComparator(Question question) {
+    this.question = question;
+  }
+
+  @Override
+  public int compare(Course o1, Course o2) {
+    double diff = o2.getAverageScore(question) - o1.getAverageScore(question);
+    return (int) (diff < 0 ? Math.floor(diff) : Math.ceil(diff));
+  }
+
+
+}