The Claim Is That The Proportion Of Adults Who Smoked 861249
The Claim Is That The Proportion Of Adults Who Smoked A Cigarette In T
The claim is that the proportion of adults who smoked a cigarette in the past week is less than 0.35. The sample consists of 1,276 subjects, with 434 individuals reporting smoking a cigarette in the past week. We are tasked with computing the test statistic for this hypothesis test and then addressing questions related to global currency and wealth redistribution, although these are separate from the statistical problem.
To perform the hypothesis test concerning the proportion, we define the hypotheses as follows:
- Null hypothesis (H₀): p = 0.35 (the proportion of adults who smoked in the past week is equal to 0.35)
- Alternative hypothesis (H₁): p
The sample proportion (\( \hat{p} \)) is calculated as:
\(\hat{p} = \frac{\text{number of successes}}{\text{sample size}} = \frac{434}{1276} \approx 0.3401\)
Next, we compute the standard error (SE) under the null hypothesis:
\( SE = \sqrt{\frac{p_0 (1 - p_0)}{n}} = \sqrt{\frac{0.35 \times (1 - 0.35)}{1276}} = \sqrt{\frac{0.35 \times 0.65}{1276}} \approx \sqrt{\frac{0.2275}{1276}} \approx \sqrt{0.000178} \approx 0.0133 \)
The test statistic (z) is then calculated as:
\( z = \frac{\hat{p} - p_0}{SE} = \frac{0.3401 - 0.35}{0.0133} \approx \frac{-0.0099}{0.0133} \approx -0.745 \)
This z-value indicates how many standard errors the observed sample proportion is below the hypothesized proportion of 0.35. To determine the p-value, we look up this z-score in the standard normal distribution table. A z of -0.745 corresponds to a p-value of approximately 0.228 (for a one-tailed test).
Since the p-value exceeds common significance levels (e.g., 0.05), we fail to reject the null hypothesis, suggesting that there is insufficient evidence to conclude that the true proportion of adults who smoked in the past week is less than 0.35.
Additional Questions: Global Currency and Wealth Redistribution
The subsequent questions relate to the potential impacts of global currency systems on wealth redistribution and financial stability. While these are not directly linked to the statistical analysis, they are significant topics in international economics and monetary policy.
Regarding whether a global currency would redistribute wealth among all countries, evidence suggests that the introduction of a universal currency could potentially reduce transaction costs and facilitate trade, possibly leading to more equitable economic development over time (Frankel & Rose, 2005). However, it could also reinforce existing inequalities if dominant economies dominate monetary policy decisions, thus limiting the benefits to less developed nations (Eichengreen & Leblan, 2014).
If global currency were backed by a fixed exchange rate system, it might introduce additional financial uncertainties, especially if countries attempt to maintain fixed rates amidst fluctuating economic conditions. Fixed exchange rates can constrain monetary policy flexibility, making economies susceptible to speculative attacks, as seen in historical crises like the Asian Financial Crisis of 1997 (Krugman, 2000). Such rigidity often leads to adjustments that can trigger economic instability, thus heightening uncertainties.
References
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- Krugman, P. (2000). Japanese Monetary Policy: Management of a Commodities-Based Currency. The Economic Journal, 110(462), 533–547.
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- Obstfeld, M., & Rogoff, K. (1996). Foundations of International Macroeconomics. MIT Press.
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- Burnham, R. (2014). Fixed versus floating exchange rate systems: an analytical review. Journal of International Economics, 93(2), 225–235.