ChiSquareTest Class

[SerializableAttribute]
public class ChiSquareTest : HypothesisTest<ChiSquareDistribution>

<SerializableAttribute>
Public Class ChiSquareTest
	Inherits HypothesisTest(Of ChiSquareDistribution)

// Suppose we would like to test the hypothesis that a random sample of 
// 100 people has been drawn from a population in which men and women are
// equal in frequency. 

// Under this hypothesis, the observed number of men and women would be 
// compared to the theoretical frequencies of 50 men and 50 women. So,
// after drawing our sample, we found out that there were 44 men and 56
// women in the sample:

//                     man  woman
double[] observed = {  44,   56  };
double[] expected = {  50,   50  };

// If the null hypothesis is true (i.e., men and women are chosen with 
// equal probability), the test statistic will be drawn from a chi-squared
// distribution with one degree of freedom. If the male frequency is known, 
// then the female frequency is determined.
// 
int degreesOfFreedom = 1;

// So now we have:
// 
var chi = new ChiSquareTest(expected, observed, degreesOfFreedom);


// The chi-squared distribution for 1 degree of freedom shows that the 
// probability of observing this difference (or a more extreme difference 
// than this) if men and women are equally numerous in the population is 
// approximately 0.23. 

double pvalue = chi.PValue; // 0.23

// This probability is higher than conventional criteria for statistical
// significance (0.001 or 0.05), so normally we would not reject the null
// hypothesis that the number of men in the population is the same as the
// number of women.

bool significant = chi.Significant; // false