Sunday, April 1, 2012

Lessons from Statistics

For the past few weeks I've been statistically analyzing participants' answers to the pre and post test to evaluate if the audio program resulted in changes in knowledge, beliefs, benefits, barriers, and intention to exclusively breastfeed.  One of my options in analyzing the data was to collapse all of the participants answers into dichotomous data (yes, no answers).  Initially this seemed like a simple, straightforward way to determine if the intervention worked--either participants improved their knowledge as a result of listening to the program or they didn't.  Thinking about analyzing the data this way made me think about how often in life I like to look at things as yes or no, black or white, living in America or living in Cameroon.  It seems neater to divide life into two distinct categories, but as Oriah says in her book The Dance, "Neatness is really only preferable in bathrooms and in written reports" (or in my case, a dissertation).

Life isn't neat and black or white. Its lived in the midst of changes and gradients.  So instead of analyzing the data as yes or no, I sought to analyze how participants changed within a gradient.  Some drastically improved, some stayed the same, some actually decreased and overall the audio program was effective in improving knowledge and benefits, but not beliefs, barriers, or intention to exclusively breastfeed.  As I've been analyzing changes amongst the participants, I've been thinking about change in general.  Not just how to best analyze it, but the rate at which it can happen.  Today is Palm Sunday, the day in which Jesus comes triumphantly riding on a donkey amongst people shouting "Hosanna!"  Yet, a few days later, things have drastically changed as Jesus is spit upon and mocked.  Change in life is inevitable (and I think really analyzing the change is inevitable also), but I believe it also brings new insight and significance.  I know that going through the statistical analysis brought new insight to me and hopefully the changes in the participants were not just statistically signficant, but life significant.


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