1. Two examples are randomly selected from two groups of students who have been taught using different teaching methods. An examination is given and the results are shown below:
Group 1 Group 2
N1 = 8 n2 = 10
Mean of Grp 1 =85 Mean of Grp 2 =87
Variance of Grp 1 =46 Variance of Grp 2 = 36.
Using a .05 level of significance, can we conclude that the two different teaching methods are equally effective?
"H_0 : \u03bc_1 = \u03bc_2 \\\\\n\nH_1 : \u03bc_1 \u2260 \u03bc_2 \\\\\n\nn_1 = 8 \\\\\n\n\\bar{X_1} = 85 \\\\\n\ns^2_1 = 46 \\\\\n\nn_2 = 10 \\\\\n\n\\bar{X_2} = 87 \\\\\n\ns^2_2=36"
Because both samples are small (< 30), we use the t test statistic. Before implementing the formula, we first check whether the assumption of equality of population variances is reasonable. The ratio of the sample variances, "\\frac{s_1^2}{s_2^2} = \\frac{46}{36} = 1.27" , which falls between 0.5 and 2, suggesting that the assumption of equality of population variances is reasonable. The appropriate test statistic is:
"t = \\frac{\\bar{X_1} \u2013 \\bar{X_2}}{S_p \\sqrt{ \\frac{1}{n_1} + \\frac{1}{n_2}}}"
This is a two-tailed test, using a t statistic and a 5% level of significance. The appropriate critical value can be found in the t Table. In order to determine the critical value of t we need degrees of freedom, df, defined as df=n1+n2-2 = 8+10-2=16. The critical regions for a two-tailed test with df=16 and α=0.05 are t ≥ 1.745 and t ≤ -1.745 and the decision rule is: Reject H0 if t ≥ 1.745 or t ≤ -1.745.
We now substitute the sample data into the formula for the test statistic. Before substituting, we will first compute Sp, the pooled estimate of the common standard deviation.
"S_p = \\sqrt{ \\frac{(n_1-1)s^2_1+(n_2-1)s^2_2}{n_1+n_2-2} } \\\\\n\nS_p = \\sqrt{ \\frac{(8-1)46+(10-1)36}{8+10-2} } \\\\\n\nS_p = 6.35 \\\\\n\nt = \\frac{85 \u2013 87}{6.35 \\sqrt{ \\frac{1}{8} + \\frac{1}{10}}} = -0.66"
Since -0.66 > -1.745, we cannot reject the null hypothesis.
Using a 0.05 level of significance, we can conclude that the two different teaching methods are equally effective.
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