# (i) First use the data set 401KSUBS.RAW, keeping only observations with fsize = 1. Find the skewness measure for inc. Do the same for log(mc). Which variable has more skewness and therefore seems less likely to be normally distributed?(ii) Next use BWGHT2.RAW. Find the skewness measures for bwght and log(bwght). What do you conclude?(iii) Evaluate the following statement: The logarithmic

(i) First use the data set 401KSUBS.RAW, keeping only observations with fsize = 1. Find the skewness measure for inc. Do the same for log(mc). Which variable has more skewness and therefore seems less likely to be normally distributed?

(ii) Next use BWGHT2.RAW. Find the skewness measures for bwght and log(bwght). What do you conclude?

(iii) Evaluate the following statement: "The logarithmic transformation always makes a positive variable look more normally distributed."

(iv) If we are interested in the normality assumption in the context of regression, should we be evaluating the unconditional distributions of y and Iog(y)? Explain.

(ii) Next use BWGHT2.RAW. Find the skewness measures for bwght and log(bwght). What do you conclude?

(iii) Evaluate the following statement: "The logarithmic transformation always makes a positive variable look more normally distributed."

(iv) If we are interested in the normality assumption in the context of regression, should we be evaluating the unconditional distributions of y and Iog(y)? Explain.

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**Related Book For**

## Introductory Econometrics A Modern Approach

4th edition

Authors: Jeffrey M. Wooldridge

ISBN: 978-0324660548