The formula for degrees of freedom when population standard deviations are not assumed to be equal is:
$df = \frac{(\frac{s_1^2}{n_1} + \frac{s_2^2}{n_2})^2}{\frac{(\frac{s_1^2}{n_1})^2}{n_1 - 1} + \frac{(\frac{s_2^2}{n_2})^2}{n_2 - 1}}$
Plugging in the values from the table:
$df = \frac{(\frac{0.55^2}{47} + \frac{0.96^2}{41})^2}{\frac{(\frac{0.55^2}{47})^2}{47 - 1} + \frac{(\frac{0.96^2}{41})^2}{41 - 1}} = \frac{(0.0064468 + 0.0225268)^2}{\frac{0.0000406}{46} + \frac{0.0005308}{40}} = \frac{0.0008362}{0.00000088 + 0.00001327} \approx \frac{0.0008362}{0.00001415} \approx 59.06 \approx 59$
Since we weren't given a confidence level, we'll assume a 95% confidence level. With df = 59 and α = 0.05 (two-tailed), the t-score is approximately 2.00. This value can be found using a t-table or a statistical calculator.
The margin of error is calculated as:
$E = t \sqrt{\frac{s_1^2}{n_1} + \frac{s_2^2}{n_2}} = 2.00 \sqrt{\frac{0.55^2}{47} + \frac{0.96^2}{41}} = 2.00 \sqrt{0.006447 + 0.022527} \approx 2.00 \sqrt{0.028974} \approx 2.00 * 0.1702 \approx 0.340$
The confidence interval is calculated as:
$(\bar{x}_1 - \bar{x}_2) \pm E = (3.53 - 2.71) \pm 0.340 = 0.82 \pm 0.340$
So, the confidence interval is (0.48, 1.16).