To determine the 90% confidence interval for the mean \(\theta\) based on a sample from a normal distribution with unknown mean and variance, we shall use the t-distribution. Here, the sample mean \(\overline{x} = 0\), and the sample standard deviation \(s = 2\). The degrees of freedom for our sample size of 10 is \(n-1 = 9\).
The formula for the confidence interval is given by:
\(CI = \left( \overline{x} - t_{\alpha/2} \cdot \frac{s}{\sqrt{n}}, \overline{x} + t_{\alpha/2} \cdot \frac{s}{\sqrt{n}} \right)\)
where \(t_{\alpha/2}\) is the t-value for a 90% confidence interval with 9 degrees of freedom. For 90% confidence, each tail of the distribution covers 5%, hence we look for the t-value corresponding to 0.05 (this value can be looked up in the t-distribution table or calculated using statistical software). For 9 degrees of freedom, this is approximately 1.833.
Substituting the values:
Calculate the interval:
\(CI = \left( 0 - 1.833 \cdot \frac{2}{\sqrt{10}}, 0 + 1.833 \cdot \frac{2}{\sqrt{10}} \right)\)
Simplify:
\(CI = \left( 0 - \frac{3.666}{\sqrt{10}}, 0 + \frac{3.666}{\sqrt{10}} \right)\)
Approximating further:
\(CI = \left( 0 - 1.1587, 0 + 1.1587 \right)\)
Therefore, the 90% confidence interval for \(\theta\) is \((-1.1587, 1.1587)\).
Choice analysis:
Thus, the correct confidence interval is (-1.1587, 1.1587).