Chi-Square Test
• Formalizes this notion of distribution fit
– Oi represents the number of observed data values in the i-th interval.
– pi is the probability of a data value falling in the i-th interval under the hypothesized distribution.
– So we would expect to observe Ei = npi, if we have n observations
So the chi-squared statistic is
• So the hypotheses are
– H0: the random variable, X, conforms to the distributional assumption with parameters given by the parameter estimates.
– H1: the random variable does not conform.
C Program For Chi-Square Test
#include<stdio.h>
int main()
{
int n,i,e,calc=0,z=16.9;
printf("Total number : ");
scanf("%d",&n);
int arr[n],o[10]={0,0,0,0,0,0,0,0,0,0},oo[10],ooo[10];
printf("Enter %d number : ",n);
for(i=0;i<n;i++)
{
scanf("%d",&arr[i]);
}
for(i=0;i<n;i++)
{
if(arr[i]<10)
o[0]++;
else if(arr[i]<20 && arr[i]>=10)
o[1]++;
else if(arr[i]<30 && arr[i]>=20)
o[2]++;
else if(arr[i]<40 && arr[i]>=30)
o[3]++;
else if(arr[i]<50 && arr[i]>=40)
o[4]++;
else if(arr[i]<60 && arr[i]>=50)
o[5]++;
else if(arr[i]<70 && arr[i]>=60)
o[6]++;
else if(arr[i]<80 && arr[i]>=70)
o[7]++;
else if(arr[i]<90 && arr[i]>=80)
o[8]++;
else
o[9]++;
}
e=n/10;
for(i=0;i<10;i++)
{
oo[i]=(o[i]-e)*(o[i]-e);
ooo[i]=oo[i]/e;
calc=calc+ooo[i];
}
if(calc<=z)
printf("Null hypo accepted. The value are uniformly distributed.");
else
printf("Alt hypo accepted. The value are not uniformly distributed.");
return 0;
}
Post A Comment:
0 comments so far,add yours