There is an interesting exercise you might come across if you ever happen to find yourself engaged in an ethical debate over responsibility or blame. The exercise involves listening to a story and then assigning a degree of culpability to everyone in the story for its tragic end result. The story goes like this:
A married woman feels neglected by her hard-working husband, who travels a lot for his job, so when she meets another man who invites her to his house, she spends the night and the following morning rushes home to greet her husband before he arrives back from his latest business trip, but the bridge she needs to cross to get home is blocked by a madman “who kills everyone who comes near him.”
The young wife follows the river and meets a ferryman, but he demands $10 to take her to the other side. The young wife has no money. She runs back to her lover and asks for the $10, but he refuses. The woman then remembers a platonic friend who lives nearby. She runs to him, explains her plight. The friend refuses to help because he is disillusioned by her involvement with another man. Her only choice is to go by the bridge, in spite of the danger, and the madman kills her.
You might be surprised by some of the responses you would come across, but before you start ranking these characters yourself, let’s put a positive spin on the discussion by changing blame to responsibility and changing the tragedy to triumph. As Eston Martz asks of us in this month’s Quality 101:
Imagine a football game: If one player tackles the quarterback, it’s easy to give credit for the sack where credit’s due. But if three players tackle the quarterback simultaneously, it’s much more difficult to determine who was most responsible.
Martz provides yet another example:
Or imagine seeing a rock and roll band with two great guitar players. You want to see which one plays best. But on stage, they’re both playing loud and fast. What they’re doing is so similar it’s difficult to tell one from the other. So how can you tell which guitarist has the biggest effect on the sound?
What Eston is trying to get us to consider is multicollinearity and “the use of regression analysis to explore the relationships between one or more input variables, or factors, and a response.”
As Martz puts it, “a manufacturer might use it to look at how baking time and temperature relate to the hardness of a piece of plastic. Social scientists might use it to see how educational levels and birthplace relate to annual income. In theory, the number of factors you could include in a regression model is limited only by your imagination.”
Although it may not answer ethical questions such as the one posed earlier, software can be used to solve a range of problems. So find out more about multicollinearity with this month’s Quality 101, “When More is Not Better.”
Enjoy and thanks for reading!