The U.S. federal ban on assault weapons expired in September 2004, which meant that after 10 years (since the ban was instituted in 1994) there were certain types of guns that could be manufactured legally again. A poll asked a random sample of 1,200 eligible voters (among other questions) whether they were satisfied with the fact that the law had expired. The datafile linked below contains the results of this poll (Data were generated based on a poll conducted by NBC News/Wall Street Journal Poll). We would like to estimate p, the proportion of U.S. eligible voters who were satisfied with the expiration of the law, with a 95% confidence interval.

M.E.= 2.9%

(a) How many of the 1,200 sampled voters were satisfied?

(b) What is the sample proportion (p-hat) of those who were satisfied?

(c) What is the 95% confidence interval for p? Interpret this interval.

In question 1 you found that the margin of error of this poll was about 2.9%. What is the margin of error of the confidence interval you found in question 2?

Volkswagen saw a 95% drop in its fourth quarter profits in 2004 after an unexpected surge in the value of the Euro left the company with losses of $1.5 billion.

1. What is hedging? Explain how Volkswagen's failure to fully protect itself against foreign exchange fluctuations had a negative effect on the company? What can Volkswagen and other companies learn from this experience?

2. Why was Volkswagen so vulnerable to the change in the value of the Euro against the US Dollar relative to the US Dollar?

3. In 2015 and 2016 strong dollar affected several US companies. Please see the one of the examples in the following links (2015 and 2016) where the strong dollar hurt the company. What can this company do to protect itself from exchange rate fluctuations? Since the beginning of 2017, the dollar has been weakening. What does that mean for US companies? How will the weaker dollar affect US businesses?  

only need to anwser to question 3

Moretti (2004) finds that higher education has significant positive externalities on wages of all workers. This suggests that

Group of answer choices

High skill and low skill workers are complements in production.

A larger share of workers with higher education causes employers to choose labor-biased technology.

A larger share of workers with higher education increases the productivity of all human capital levels.

Workers can 'pick up' human capital from working with high skill co-workers.

Membrane Protein Census

(a) Table 1 of Mitra et al. (2004) reports the mass ratio of proteins and phospholipids in the membranes of various cells and organelles. Use the asserted 2.0mg of protein for every 1.0mg of phospholipid in the E. coli membrane to compute the areal density of membrane proteins and their mean spacing. Make a corresponding estimate for the membrane of the endoplasmic reticulum using the fact that the mass ratio in this case is 2.6. Explain all of you assumptions in making the estimate.

(b) Dupuy and Engelman (2008) report that the area fraction associated with membrane proteins in the red blood cell membrane is roughly 23%, while the lipids themselves take up roughly 77% of the membrane area. Use these numbers to estimate the number of membrane proteins in the red blood cell membrane and their mean spacing. Explain all theassumptions you make in constructing the estimate.

A particular report from 2004 classified 721 fatal bicycle accidents according to the month in which the accident occurred, resulting in the accompanying table.

(a) Use the given data to test the null hypothesis H₀: ?₁ = 1/12, ?₂ = 1/12, . . . , ?₁₂ = 1/12, where ?₁ is the proportion of fatal bicycle accidents that occur in January, ?₂ is the proportion for February, and so on. Use a significance level of 0.01. (Use 2 decimal places.)
?² =  

(b) The null hypothesis in Part (a) specifies that fatal accidents were equally likely to occur in any of the 12 months. But not all months have the same number of days. Test the hypotheses proposed in H₀: ?₄ = ?₆ = ?₉ = ?₁₁ =

? 0.082, ?₂ =

? 0.079, ?₁ = ?₃ = ?₅ = ?₇ = ?₈ = ?₁₀ = ?₁₂ =

? 0.085 using a 0.05 significance level. (Use 2 decimal places.)
?² =  

1. In 2004, the University of California education system drastically cut enrollment due to significant state budget cuts and asked 7,600 applicants to defer enrollment for two years after completing two years at a community college. Tuition costs remained fixed by the state.
   • Demonstrate the situation described with supply and demand curves, carefully labeling any excess supply or demand for college admission.
   • What is the market solution to the excess demand for college?
   • What is a possible reason the market solution was not pursued?

In 2004, Congress allocated over $20 billion to fight illegal drugs. About 60 percent of the funds were directed at reducing the supply of drugs through domestic law enforcement and interdiction. Some critics of this approach argue that supply-side approaches to reduce the drug supply actually helped drug producers.

• Demonstrate graphically the effect of supply-side measures on the market for illegal drugs.
• Explain how these measures affect drug producers. (Hint: Consider the elasticity of demand).
• Demonstrate the effect of demand-side measures such as treatment and prevention on the market for illegal drugs.
• How does the shift in demand affect the profitability of producers?
• submit your graph as a jpg attachment in your original discussion post

In August 2004, Bonnie Martin bought a house for $391,000. She put 20% down and financed the rest with a thirty-year loan at the then-current rate of 5 3 4 %. In 2007, the real estate market crashed. In June 2009, she had to sell her house. The best she could get was $235,000. Was this enough to pay off the loan?I got no. If so, how much did she profit? If not, how much did she have to pay out of pocket to pay off the loan? (Round your answer to the nearest cent.) I got 76150.53 which is incorrect

Amstat News (December 2004) lists median salaries for associate professors of statistics at research institutions and at liberal arts and other institutions in the United States. Assume a sample of 200 associate professors from research institutions having an average salary of $70,750 per year with a standard deviation of $6000. Assume also a sample of 200 associate professors from other types of institutions having an average salary of $65,200 with a standard deviation of $5000. Test the hypothesis that the mean salary for associate professors in research institutions is $2000 higher than for those in other institutions. Use a 0.01 level of significance.

confused for what the alternative hypothesis is...