"\\begin{matrix}\n No.of\\ boys & 0 & 1 & 2 & 3 & 4 \\\\\n No.of\\ girls & 4 & 3 & 2 & 1 & 0 \\\\\n No.of\\ families & 32 & 178 & 290 & 236 & 64\n\\end{matrix}"
"P(all\\ boys)=(\\dfrac{1}{2})^4=\\dfrac{1}{16}"
"P(3\\ boys\\ \\& \\ 1\\ girl)=\\dbinom{4}{3}(\\dfrac{1}{2})^3(\\dfrac{1}{2})=\\dfrac{1}{4}"
"P(2\\ boys\\ \\& \\ 2\\ girl)=\\dbinom{4}{2}(\\dfrac{1}{2})^2(\\dfrac{1}{2})^2=\\dfrac{3}{8}"
"P(1\\ boy\\ \\& \\ 3\\ girls)=\\dbinom{4}{1}(\\dfrac{1}{2})(\\dfrac{1}{2})^3=\\dfrac{1}{4}"
"P(all\\ girls)=(\\dfrac{1}{2})^4=\\dfrac{1}{16}"
For 800 families
"No.of\\ families(all\\ boys)=\\dfrac{1}{16}\\times800=50"
"No.of\\ families(3\\ boys\\ \\& \\ 1\\ girl)=\\dfrac{1}{4}\\times800=200"
"No.of\\ families(2\\ boys\\ \\& \\ 2\\ girl)=\\dfrac{3}{8}\\times800=300"
"No.of\\ families(1\\ boy\\ \\& \\ 3\\ girls)=\\dfrac{1}{4}\\times800=200"
"No.of\\ families(all\\ girls)=\\dfrac{1}{16}\\times800=50"
"H_0:" the male & female births are equally probable.
Based on the information provided, the significance level is "\\alpha=0.05," the number of degrees of freedom is "df=5-1=4," so then the rejection region for this test is "R=\\{\\chi^2:\\chi^2>9.488\\}."
The Chi-Squared statistic is computed as follows:
"=\\dfrac{(32-50)^2}{50}+\\dfrac{(178-200)^2}{200}+\\dfrac{(290-300)^2}{300}+"
"+\\dfrac{(236-200)^2}{200}+\\dfrac{(64-50)^2}{50}=\\dfrac{589}{30}\\approx19.633"
Since it is observed that "\\chi^2=19.6333>9.488=\\chi_c^2," it is then concluded that the null hypothesis is rejected.
Therefore, there is enough evidence to claim that the male & female births are not equally probable,at the "\\alpha=0.05" significance level.
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