Step 1 :Define the sample size, n = 3643, and the number of successes, x = 1759.
Step 2 :Calculate the sample proportion, \(p_{hat} = \frac{x}{n} = \frac{1759}{3643} = 0.483\).
Step 3 :Define the proportion in the null hypothesis, p0 = 0.46.
Step 4 :Calculate the z-score using the formula \(z = \frac{p_{hat} - p0}{\sqrt{\frac{p0 * (1 - p0)}{n}}} = \frac{0.483 - 0.46}{\sqrt{\frac{0.46 * (1 - 0.46)}{3643}}} = 2.77\).
Step 5 :Since the z-score is greater than the critical value of 1.96 for a 95% confidence level, we reject the null hypothesis and conclude that the proportion of site users who get their world news on this site has changed since 2013.
Step 6 :Calculate the 95% confidence interval for the population proportion using the formula \(p_{hat} \pm z_{95} * \sqrt{\frac{p_{hat} * (1 - p_{hat})}{n}}\), where \(z_{95} = 1.96\).
Step 7 :The lower bound of the confidence interval is \(0.483 - 1.96 * \sqrt{\frac{0.483 * (1 - 0.483)}{3643}} = 0.467\).
Step 8 :The upper bound of the confidence interval is \(0.483 + 1.96 * \sqrt{\frac{0.483 * (1 - 0.483)}{3643}} = 0.499\).
Step 9 :Since the 95% confidence interval (0.467, 0.499) does not contain the value 0.46 (the proportion in 2013), this supports our conclusion from the hypothesis test that the proportion has changed.
Step 10 :Final Answer: \(\boxed{\text{a. Reject } H_{0}. \text{ The percentage is significantly different from } 46 \%.}\)
Step 11 :Final Answer: \(\boxed{\text{b. The } 95 \% \text{ confidence interval for the population proportion is } (0.467, 0.499).}\)