Summary of the above information.
"n_1=20,\\space \n\\bar{x}_1=11.13,\\space \nS_1=3.2"
"n_2=17,\\space \\bar{x}_2=12.98,\\space s_2=4.1"
The hypothesis to be tested are,
"H_0:\\mu_1=\\mu_2"
"Against"
"H_1:\\mu_1\\not=\\mu_2"
Since the study assumes that the population variances are equal, we shall apply the student's t distribution as described below.
The test statistic is given as,
"t^*=(\\bar{x}_1-\\bar{x}_2)\/\\sqrt{Sp^2*(1\/n_1+1\/n_2)}" where "Sp^2" is the pooled sample variance given by the formula,
"Sp^2=((n_1-1)*S_1^2+(n_2-1)*S_2^2)\/(n_1+n_2-2)"
"Sp^2=((19*3.2^2)+(16*4.1^2))\/(20+17-2)"
"Sp^2=(194.56+268.96)\/35=463.52\/35=13.2434286"
Now,
"t^*=(11.13-12.98)\/\\sqrt{13.24*(1\/20+1\/17)}"
"t^*=-1.85\/\\sqrt{1.441197}"
"t^*=-1.541027"
We compare "t^*" with the t-table value "(t)" with at "\\alpha" level of significance with "(n_1+n_2-2)=(20+17-2)=35" degrees of freedom and reject the null hypothesis if "|t^*|\\gt t_{\\alpha\/2,35}" .
The table value"(t)" is, "t_{\\alpha\/2,df}=t_{0.05\/2,35}=t_{0.025,35}=2.030108".
Since "|t^*|=1.541027\\lt t_{0.025,35}=2.030108", we fail to reject the null hypothesis and we conclude that there is no sufficient evidence to show that the newly-developed alloy is significantly different from the common steel.
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