In: Statistics and Probability
Let X equal the number of chocalate chips in a chocalate chip cookie. Sixty-two oberservations of X yielded the following frequencies for the possible outcomes of X:
| Outcome (x) | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 
| Frequency | 0 | 0 | 2 | 8 | 7 | 13 | 13 | 10 | 4 | 4 | 1 | 
(a) Use this data to graph the relative frequency histogram and the Poisson probability with
lamda = 5.6 on the same figure.
(b) Do these data seem to be observations of a Poisson random variable with
lamda = 5.6 ?
| x | f(x) | Relative frequency=f(x)/sum(f(x)) | Poisson probbaility | 
| 0 | 0 | 0.000 | 0.003697864 | 
| 1 | 0 | 0.000 | 0.020708037 | 
| 2 | 2 | 0.032 | 0.057982503 | 
| 3 | 8 | 0.129 | 0.108234006 | 
| 4 | 7 | 0.113 | 0.151527608 | 
| 5 | 13 | 0.210 | 0.169710921 | 
| 6 | 13 | 0.210 | 0.15839686 | 
| 7 | 10 | 0.161 | 0.126717488 | 
| 8 | 4 | 0.065 | 0.088702241 | 
| 9 | 4 | 0.065 | 0.055192506 | 
| 10 | 1 | 0.016 | 0.030907803 | 
| sum(f(X))= | 62 | 
note: To calculate poission probbailities we use the following formula:


b) To test whether the observations are from the poisson distribution we use the chi square goodness of fit test which is given as:

Where:
~
Where n= no. of observations=11
| Oi | Ei | (Oi-Ei)^2/Ei | 
| 0 | 0.003698 | 0.004 | 
| 0 | 0.020708 | 0.021 | 
| 0.032258 | 0.057983 | 0.011 | 
| 0.129032 | 0.108234 | 0.004 | 
| 0.112903 | 0.151528 | 0.010 | 
| 0.209677 | 0.169711 | 0.009 | 
| 0.209677 | 0.158397 | 0.017 | 
| 0.16129 | 0.126717 | 0.009 | 
| 0.064516 | 0.088702 | 0.007 | 
| 0.064516 | 0.055193 | 0.002 | 
| 0.016129 | 0.030908 | 0.007 | 
 = | 
0.100 | 

Since calculated 
 (4.57) at 5% level of significance we conclude that the data seem
to be observations of poission random variable with lamda =5.6