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Statistics : Point Estimates and Confidence Intervals

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Many stock market observers say that when the p/e ratio for stocks gets over 20 the market is overvalued. (the p/e ratio is stock price divided by the most recent 12 months of earnings.) Suppose you are interested in seeing whether the current market is overvalued and would also like to know the proportion of companies that pay dividends. (use attached file: NYSEStocks, a random sample of 30 companies).

a. What is a point estimation of the p/e ratio for the population of stocks listed on the NYSE? Develop a 95% confidence interval.

b. Based on answer to part (a.) above is the market overvalued or not? Why or why not?

c. What is a point estimate of the proportion of companies on the NYSE that pay dividends? Is the sample size large enough to justify using the normal distribution to construct a confidence interval for this proportion? Why or why not?

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Solution Summary

Point estimates and confidence intervals are investigated. The solution is detailed and well presented.

Solution provided by:
Changping Wang, MA
Education
  • BSc , Wuhan Univ. China
  • MA, Shandong Univ.
Recent Feedback
  • "Your solution, looks excellent. I recognize things from previous chapters. I have seen the standard deviation formula you used to get 5.154. I do understand the Central Limit Theorem needs the sample size (n) to be greater than 30, we have 100. I do understand the sample mean(s) of the population will follow a normal distribution, and that CLT states the sample mean of population is the population (mean), we have 143.74. But when and WHY do we use the standard deviation formula where you got 5.154. WHEN & Why use standard deviation of the sample mean. I don't understand, why don't we simply use the "100" I understand that standard deviation is the square root of variance. I do understand that the variance is the square of the differences of each sample data value minus the mean. But somehow, why not use 100, why use standard deviation of sample mean? Please help explain."
  • "excellent work"
  • "Thank you so much for all of your help!!! I will be posting another assignment. Please let me know (once posted), if the credits I'm offering is enough or you ! Thanks again!"
  • "Thank you"
  • "Thank you very much for your valuable time and assistance!"
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