Common errors in statistics

Phillip Good and James Hardin often succeed in their endeavor to make their content accessible to an audience beyond that of "hardcore" statisticians. Despite their many applications in any modern society, statistics look unappealing to most people. Sometimes, both authors get lost in esoteric debates about some statistical topics that are of limited interest to a wider audience. Furthermore, Good and Hardin give too many examples that are related to the medical field. The authors could diversify their examples in a fourth edition of their treatise to further expand their readership. To their credit, Good and Hardin repeatedly warn their audience against the servile reliance on statistical software. Software users have to check the default settings to see if they are applicable to the application at hand. The authors correctly note that the most common error in statistics is to assume that statistical procedures can take the place of sustained effort. For this reason, Good and Hardin urge their readers not to let statistics and by extension statistical software do their thinking for them. In conclusion, "Common Errors in Statistics (and How to Avoid Them)" is a nice addition to anyone's modeling / statistical library.