ECN 221 ASU FINAL EXAM QUESTIONS AND CORRECT
ANSWERS LATEST UPDATE
The numerical value of the standard deviation can never be
larger than the variance
negative
zero
all of the answers are correct ANSWER negative
The mean of a standard normal probability distribution
-Can be any value
-None of the answers is correct.
-Is always equal to 1
-can take any value provided it is positive - ANSWER -none of the answers is correct.
The difference between the number of total observations (N) and the number of
estimated coefficients (beta-hats) provides the number of:
-residuals
-independent variables
-viable observations
-degrees of freedom - ANSWER degrees of freedom
the interquartile range is used as a measure of variability to overcome what difficulty of
the range?
the range is influenced too much by extreme values
the range is difficult to compute
the sum of the range variances is zero
, -the range is negative-ANSWER the range is influence too much by extreme values
In statistics, IQR stands for
- Individual quartile relativity
- Individual quantity range
- Inter-quartile range
- Inter-quantity relativity - ANSWER inter-quartile range
Revised probabilities of events based upon additional information are
-Marginal probabilities
-Complementary probabilities
-Posterior probabilities
-Joint probabilities - ANSWER posterior probabilities
The R-squared statistic is calculated as
-the explained sum of squares (ESS) divided by the residual sum of squares (RSS)
-the residual sum of squares (RSS) divided by the total sum of squares (RSS)
-the explained sum of squares (ESS) divided by the total sum of squares (TSS)
-the total sum of squares (TSS) divided by the residual sum of squares (RSS) - ANSWER
the explained sum of squares (ESS) divided by the total sum of squares (TSS)
The total sum of squares (TSS) is equal to:
-the explained sum of squares (ESS) times the residual sum of squares (RSS)
-the explained sum of squares (ESS) divided by the residual sum of squares (RSS)
-the explained sum of squares (ESS) minus the residual sum of squares (RSS)
-the explained sum of squares ESS plus the residual sum of squares RSS
the explained sum of squares ESS plus the residual sum of squares RSS
ANSWERS LATEST UPDATE
The numerical value of the standard deviation can never be
larger than the variance
negative
zero
all of the answers are correct ANSWER negative
The mean of a standard normal probability distribution
-Can be any value
-None of the answers is correct.
-Is always equal to 1
-can take any value provided it is positive - ANSWER -none of the answers is correct.
The difference between the number of total observations (N) and the number of
estimated coefficients (beta-hats) provides the number of:
-residuals
-independent variables
-viable observations
-degrees of freedom - ANSWER degrees of freedom
the interquartile range is used as a measure of variability to overcome what difficulty of
the range?
the range is influenced too much by extreme values
the range is difficult to compute
the sum of the range variances is zero
, -the range is negative-ANSWER the range is influence too much by extreme values
In statistics, IQR stands for
- Individual quartile relativity
- Individual quantity range
- Inter-quartile range
- Inter-quantity relativity - ANSWER inter-quartile range
Revised probabilities of events based upon additional information are
-Marginal probabilities
-Complementary probabilities
-Posterior probabilities
-Joint probabilities - ANSWER posterior probabilities
The R-squared statistic is calculated as
-the explained sum of squares (ESS) divided by the residual sum of squares (RSS)
-the residual sum of squares (RSS) divided by the total sum of squares (RSS)
-the explained sum of squares (ESS) divided by the total sum of squares (TSS)
-the total sum of squares (TSS) divided by the residual sum of squares (RSS) - ANSWER
the explained sum of squares (ESS) divided by the total sum of squares (TSS)
The total sum of squares (TSS) is equal to:
-the explained sum of squares (ESS) times the residual sum of squares (RSS)
-the explained sum of squares (ESS) divided by the residual sum of squares (RSS)
-the explained sum of squares (ESS) minus the residual sum of squares (RSS)
-the explained sum of squares ESS plus the residual sum of squares RSS
the explained sum of squares ESS plus the residual sum of squares RSS
