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发表于 2011-3-3 11:19 | 只看该作者

Reading 11: Correlation and Regression-LOS b 习题精选

2011, including, center, style
Session 3: Quantitative Methods for Valuation
Reading 11: Correlation and Regression

LOS b: Explain the limitations to correlation analysis, including outliers and spurious correlation.

 

 

Ron James, CFA, computed the correlation coefficient for historical oil prices and the occurrence of a leap year and has identified a statistically significant relationship. Specifically, the price of oil declined every fourth calendar year, all other factors held constant. James has most likely identified which of the following conditions in correlation analysis?

A)
 Spurious correlation.
B)
 Positive correlation.
C)
 Outliers.

 

Spurious correlation occurs when the analysis erroneously indicates a linear relationship between two variables when none exists. There is no economic explanation for this relationship; therefore this would be classified as spurious correlation.

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土豆妮

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发表于 2011-3-3 11:19 | 只看该作者

One major limitation of the correlation analysis of two random variables is when two variables are highly correlated, but no economic relationship exists. This condition most likely indicates the presence of:

A)
 outliers.
B)
 nonlinear relationships.
C)
 spurious correlation.

Spurious correlation occurs when the analysis erroneously indicates a relationship between two variables when none exists.

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土豆妮

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3#
发表于 2011-3-3 11:19 | 只看该作者

One of the limitations of correlation analysis of two random variables is the presence of outliers, which can lead to which of the following erroneous assumptions?

A)
 The presence of a nonlinear relationship between the two variables, when in fact, there is a linear relationship.
B)
 The presence of a nonlinear relationship between the two variables, when in fact, there is no relationship whatsoever between the two variables.
C)
 The absence of a relationship between the two variables, when in fact, there is a linear relationship.

Outliers represent a few extreme values for sample observations in a correlation analysis. They can either provide statistical evidence that a significant relationship exists, when there is none, or provide evidence that no relationship exists when one does.

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