To compare the results of boys and girls in a class, a special test was given to 50 boys who averaged 67.4 with Standard deviation of 5, and 50 girls averaged 62.8 with Standard deviation of 4.6.
a) Test, at alpha=0.05, whether the difference is significant or not.
b) Test if the difference is 3.0.
Boys
"n_1=50\\\\\\bar x=67.4\\\\s_1=5"
Girls
"n_2=50\\\\\\bar x_2=62.8\\\\s_2=4.6"
"a)"
We test the following hypotheses,
"H_0:\\mu_1-\\mu_2=0\\\\vs\\\\H_1:\\mu_1-\\mu_2\\not=0"
We apply t distribution to perform this test as follows,.
The test statistic is given as,
"t_c={(\\bar x_1-\\bar x_2)-(\\mu_1-\\mu_2)\\over \\sqrt{{s_1^2\\over n_1}+{s_2^2\\over n_2}}}={(67.4-62.8)-0\\over\\sqrt{{25\\over50}+{21.16\\over 50}}}={4.6\\over\\sqrt{0.9232}}={4.6\\over0.96083297}=4.7875"
"t_c" is compared with the table value at "\\alpha=0.05" with "n_1+n_2-2=50+50-2=98" degrees of freedom.
The table value is,
"t_{{0.05\\over2},98}=t_{0.025,98}=1.984467"
The null hypothesis is rejected if "|t_c|\\gt t_{0.025,98}."
Now,
"|t_c|=4.7875\\gt t_{0.025,98}=1.984467," and we reject the null hypothesis and conclude that there is sufficient evidence to show that the difference in means between boys and girls is significant at 5% level of significance.
"b)"
The hypothesis tested are,
"H_0:\\mu_1-\\mu_2=3\\\\vs\\\\H_1:\\mu_1-\\mu_2\\not=3"
"t_c={(\\bar x_1-\\bar x_2)-(\\mu_1-\\mu_2)\\over \\sqrt{{s_1^2\\over n_1}+{s_2^2\\over n_2}}}=={(67.4-62.8)-3\\over\\sqrt{{25\\over50}+{21.16\\over 50}}}={(4.6-3)\\over\\sqrt{0.9232}}={1.6\\over 0.96083297}=1.6652"
"t_c" is compared with the table value at "\\alpha=0.05" with "n_1+n_2-2=50+50-2=98" degrees of freedom.
The table value is,
"t_{{0.05\\over2},98}=t_{0.025,98}=1.984467"
The null hypothesis is rejected if "|t_c|\\gt t_{0.025,98}."
Since "|t_c|=1.6652\\lt t_{0.025,98}=1.984467," we fail to reject the null hypothesis and conclude that there is sufficient evidence to show that the difference in means between boys and girls is 3 at 5% significance level.
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