Step 1 :Given values are: sample size of night students \(n1 = 25\), sample mean GPA of night students \(x1 = 2.8\), standard deviation of night students \(s1 = 0.75\), sample size of day students \(n2 = 60\), sample mean GPA of day students \(x2 = 2.44\), standard deviation of day students \(s2 = 0.52\), and level of significance \(\alpha = 0.10\).
Step 2 :The null hypothesis \(H_0\) is that the mean GPA of night students is equal to the mean GPA of day students, i.e., \(\mu_{1} = \mu_{2}\). The alternative hypothesis \(H_a\) is that the mean GPA of night students is not equal to the mean GPA of day students, i.e., \(\mu_{1} \neq \mu_{2}\).
Step 3 :Calculate the test statistic using the formula: \(t_{stat} = \frac{x1 - x2}{\sqrt{(s1^2/n1) + (s2^2/n2)}}\). Substituting the given values, we get \(t_{stat} = 2.1906\).
Step 4 :Calculate the degrees of freedom using the formula: \(df = n1 + n2 - 2\). Substituting the given values, we get \(df = 83\).
Step 5 :Calculate the critical value using the t-distribution table with \(df = 83\) and \(\alpha = 0.10\). The critical value is \(t_{critical} = 1.6634\).
Step 6 :Since the test statistic \(t_{stat} = 2.1906\) is greater than the critical value \(t_{critical} = 1.6634\), we reject the null hypothesis \(H_0\).
Step 7 :\(\boxed{\text{Final Answer:}}\) There is enough evidence to support the claim that the mean GPA of night students is different from the mean GPA of day students.