public void compairWise(
ArrayList<Double> aList, ArrayList<Double> bList, String aGroup, String bGroup) {
// a should be the small
// b should be the larger
ArrayList<Integer> randomNumberList = new ArrayList<Integer>();
double a[] = new double[aList.size()];
double b[] = new double[aList.size()];
for (int i = 0; i < aList.size(); ) {
a[i] = aList.get(i);
while (true) {
int randomIndex = r.nextInt(bList.size());
if (!randomNumberList.contains(randomIndex)) {
randomNumberList.add(randomIndex);
b[i] = bList.get(randomIndex);
break;
}
}
i++;
}
randomNumberList.clear();
/*for(int i = 0; i<aList.size();){
System.out.println("a"+a[i]+"b"+b[i]);
}*/
int df = aList.size() + aList.size() - 2;
TTest ttest = new TTest();
System.out.println("-----------------------------");
System.out.println(bGroup + " Vs " + aGroup);
System.out.println(aGroup + " Mean:" + getMean(a));
System.out.println(aGroup + " Standard Deviation:" + getStdDev(a));
System.out.println(bGroup + " Mean:" + getMean(b));
System.out.println(bGroup + " Standard Deviation:" + getStdDev(b));
System.out.println("t_statistic:" + ttest.t(a, b));
System.out.println("p value:" + ttest.tTest(a, b));
System.out.println("DF:" + df);
double corr = new PearsonsCorrelation().correlation(a, b);
System.out.println("Correlation: " + corr);
System.out.println("\n\n");
}
public void compare() {
compairWise(toplevelList.get("Asian"), toplevelList.get("White"), "Asian", "White");
compairWise(
toplevelList.get("AfricanAmerican"), toplevelList.get("White"), "AfricanAmerican", "White");
compairWise(toplevelList.get("Hispanic"), toplevelList.get("White"), "Hispanic", "White");
compairWise(list.get("AsianM"), list.get("WhiteM"), "Asian Male", "White Male");
compairWise(list.get("AsianF"), list.get("WhiteF"), "Asian Female", "White Female");
compairWise(
list.get("AfricanAmericanM"), list.get("WhiteM"), "AfricanAmerican Male", "White Male");
compairWise(
list.get("AfricanAmericanF"), list.get("WhiteF"), "AfricanAmerican Female", "White Female");
compairWise(list.get("HispanicM"), list.get("WhiteM"), "Hispanic Male", "White Male");
compairWise(list.get("HispanicF"), list.get("WhiteF"), "Hispanic Female", "White Female");
white = new double[nonWhiteSize];
nonWhite = new double[nonWhiteSize];
ArrayList<Integer> randomNumberList = new ArrayList<Integer>();
for (int i = 0; i < nonWhiteSize; ) {
while (true) {
int randomIndex = r.nextInt(whiteSize);
if (!randomNumberList.contains(randomIndex)) {
randomNumberList.add(randomIndex);
white[i] = toplevelList.get("White").get(randomIndex);
break;
}
}
i++;
}
/*for(int i = 0; i<nonWhiteSize;){
System.out.println("Random Number:"+randomNumberList.get(i)+", white["+i+"]: "+ white[i]);
i++;
}*/
for (int i = 0; i < toplevelList.get("AfricanAmerican").size(); i++) {
nonWhite[i] = toplevelList.get("AfricanAmerican").get(i);
}
int j = 0;
for (int i = toplevelList.get("AfricanAmerican").size();
i < toplevelList.get("AfricanAmerican").size() + toplevelList.get("Asian").size();
i++) {
nonWhite[i] = toplevelList.get("Asian").get(j);
j++;
}
j = 0;
for (int i = toplevelList.get("AfricanAmerican").size() + toplevelList.get("Asian").size();
i < nonWhiteSize;
i++) {
nonWhite[i] = toplevelList.get("Hispanic").get(j);
j++;
}
int df = (int) (nonWhiteSize + nonWhiteSize - 2);
TTest ttest = new TTest();
System.out.println("-----------------------------");
System.out.println("White Vs Non-White");
System.out.println("White Mean:" + getMean(white));
System.out.println("White Standard Deviation:" + getStdDev(white));
System.out.println("Non-White Mean:" + getMean(nonWhite));
System.out.println("Non-White Standard Deviation:" + getStdDev(nonWhite));
System.out.println("t_statistic:" + ttest.t(white, nonWhite));
System.out.println("p value:" + ttest.tTest(white, nonWhite));
System.out.println("DF:" + df);
double corr = new PearsonsCorrelation().correlation(white, nonWhite);
System.out.println("Correlation: " + corr);
}
