"\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c}\n Squared\\ Distances& Boys & Girls \\\\ \\hline\n (ST) & {(30-39.375)^2\\over 39.375}=2.232 & {(30-20.625)^2\\over 20.625}=4.261 \\\\ \\hline\n (NP) & {(45-39.375)^2\\over39.375}=0.804 & {(15-20.625)^2\\over20.625}=1.534 \\\\\\hline\n (P) & {(30-26.25)^2\\over26.25}=0.536 & {(10-13.75)^2\\over13.75}=1.023 \\\\\n \n\\end{array}"
The following null and alternative hypotheses need to be tested:
"H_0:" The two variables are independent
"H_1:" The two variables are dependent
This corresponds to a Chi-Square test of independence.
Based on the information provided, the significance level is "\\alpha=0.05," the number of degrees of freedom is "df=(r-1)(c-1)=(3-1)(2-1)=2," so then the rejection region for this test is
"R=\\{\\chi^2_{(\\alpha,df)}: \\chi^2_{(\\alpha,df)}>5.991\\}"
The Chi-Squared statistic is computed as follows:
"=2.232+0.804+0.536+4.261+1.534+1.023=10.390"
Since it is observed that "\\chi^2=10.390>5.991=\\chi^2_{(\\alpha,df)}," it is then concluded that the null hypothesis is rejected.
Therefore, there is enough evidence to claim that the two variables are dependent, at the 0.05 significance level.
The corresponding p-value for the test is "p=Pr(\\chi_2^2>10.390)=0.005544."
(1) We reject the null hypothesis and conclude that specialist type and gender of children are dependent.
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