torontoanalyst

Abby Ness is an analyst for a firm that specializes in evaluating firms involved in mineral extraction. Ness believes that the earnings of copper extracting firms are more volatile than those of bauxite extraction firms. In order to test this, Ness examines the volatility of returns for 31 copper firms and 25 bauxite firms. The standard deviation of earnings for copper firms was $2.69, while the standard deviation of earnings for bauxite firms was $2.92. Ness’s Null Hypothesis is σ12 = σ22. Based on the samples, can we reject the null hypothesis at a 95% confidence level using an F-statistic and why? Null is:

A) rejected. The F-value exceeds the critical value by 0.849.

B) not rejected. The critical value exceeds the F-value by 0.71.

C) rejected. The F-value exceeds the critical value by 0.71.

---

F = s12 / s22 = $2.922 / $2.692 = 1.18
From an F table, the critical value with numerator df = 24 and denominator df = 30 is 1.89.

torontoanalyst

In order to test if Stock A is more volatile than Stock B, prices of both stocks are observed to construct the sample variance of the two stocks. The appropriate test statistics to carry out the test is the:

A) Chi-square test.

B) t test.

C) F test.

---

The F test is used to test the differences of variance between two samples.

torontoanalyst

Which of the following statements about parametric and nonparametric tests is least accurate?

A) The test of the difference in means is used when you are comparing means from two independent samples.

B) Nonparametric tests rely on population parameters.

C) The test of the mean of the differences is used when performing a paired comparison.

---

Nonparametric tests are not concerned with parameters; they make minimal assumptions about the population from which a sample comes. It is important to distinguish between the test of the difference in the means and the test of the mean of the differences. Also, it is important to understand that parametric tests rely on distributional assumptions, whereas nonparametric tests are not as strict regarding distributional properties.

torontoanalyst

Which of the following statements about parametric and nonparametric tests is least accurate?

A) Parametric tests are most appropriate when a population is heavily skewed.

B) Nonparametric tests have fewer assumptions than parametric tests.

C) Nonparametric tests are often used in conjunction with parametric tests.

---

For a distribution that is non-normally distributed, a nonparametric test may be most appropriate. A nonparametric test tends to make minimal assumptions about the population, while parametric tests rely on assumptions regarding the distribution of the population. Both kinds of tests are often used in conjunction with one another.

terpsichorefan

The hypothesis testing is the trickiest part to me..... thanks a lot!