Answer:
[tex]p_v = P(\chi^2_{11} >20.5)=0.0389[/tex]
And we can find the p value using the following excel code:
"=1-CHISQ.DIST(20.5,11,TRUE)"
Step-by-step explanation:
A chi-square goodness of fit test "determines if a sample data matches a population".
A chi-square test for independence "compares two variables in a contingency table to see if they are related. In a more general sense, it tests to see whether distributions of categorical variables differ from each another".
We need to conduct a chi square test in order to check the following hypothesis:
H0: Each month is equally likely to be the birth month for any given individual
H1: Each month is NOT equally likely to be the birth month for any given individual
The statistic to check the hypothesis is given by:
[tex]\chi^2 =\sum_{i=1}^n \frac{(O_i -E_i)^2}{E_i}[/tex]
After calculate the statistic we got [tex]\chi^2 = 20.5[/tex]
Now we can calculate the degrees of freedom for the statistic given by:
[tex]df=categories-1=12-1=11[/tex]
And we have categories =12 since we have 12 months in a year
And we can calculate the p value given by:
[tex]p_v = P(\chi^2_{11} >20.5)=0.0389[/tex]
And we can find the p value using the following excel code:
"=1-CHISQ.DIST(20.5,11,TRUE)"