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Naked With Cash is an ongoing series at Consumerism Commentary in which readers share their households’ finances with other readers. These participants benefit from the accountability that comes from tracking their finances publicly and the feedback of the four expert Certified Financial Planners (CFPs).

For more information, read this introduction.

This interview should be required listening for women — and men — who are in a relationship, particularly a marriage, in which the woman earns more than the man. This is precisely the situation in which author Farnoosh Torabi has found herself, and as a popular financial columnists, she discovered she wasn’t alone.

Based on her own experiences, questions from her readers, she began researching relationships for her latest book, When She Makes More: 10 Rules for Breadwinning Women. The book features stories from and advice for the growing number of couples who are seeing this non-traditional income dynamic.

I recently appeared on the Stacking Benjamins podcast to talk with Joe Saul-Sehy about the Debt Avalanche and the Debt Snowball, two very similar methods of paying off existing debt — usually applied to situations that involve mutiple credit cards. They two approaches differ in one important aspect, and I’ve discussed that in detail on Consumerism Commentary.

Whether you’re making a decision that has apparent, immediate consequences that could affect the rest of your life, like deciding to quit your job and open a business, or making a purchasing decision big or small, it is worthwhile to gather information and think about the future. When you gather information, you have to be careful, because people, businesses, and even statistics that provide that information might contain inherent biases.

Survivorship bias is often hidden in plain sight, but recognizing the bias when it exists could be the difference between building wealth over the long term and going broke. If a logical argument neglects to recognize that failure is a possible outcome, the argument may be subject to survivorship bias. If a statistic reflects the outcome of only the successful set, ignoring the set of those who fail, survivorship bias is at play, and can give someone a false understanding of the data.