### Discounting Weak Evidence

One pitfall to avoid is prematurely discounting seemingly weak evidence. Weak evidence can take many forms. It could be evidence that seems very unlikely under all hypotheses. Or it could be evidence that is non-intuitive and doesn’t seem to fit what we consider “conclusive” evidence.

When evaluating evidence, it’s easy to get distracted looking for “irrefutable” evidence (more on that in an upcoming blog post). However, that’s a mistake. What’s really important is the ratio between how likely evidence is under the hypotheses.

### Strength in Numbers

How much does a snowflake weigh? How about a drop of water? If you’ve ever shoveled snow, or picked up a large jug of water, you know that the weight adds up. The same principle holds true with evaluating evidence. When starting an analysis, we often find little hints that slightly support one hypothesis over the other. Many people might think that these clues wouldn’t really have an impact. Or they might assume that a piece of evidence with a significant influence on the hypotheses renders other evidence meaningless.

However, just like snow, those little pieces of evidence can add up. It’s hard to shovel up thousands of snowflakes at a time (even though individually they’re almost weightless). Likewise, enough evidence pointing in the same direction can have a weighty influence (even if each individual “proof” is not that strong independently).

On Monday, John went to the mall. John left Green’s Grocery at 7:47 AM and drove home in his 2007 Honda Pilot. John forgot his blue umbrella in the store. That night John’s neighbor Martha, a retired engineer who lives down the block from him, called him. Martha had found the umbrella and was coming to return it. Is that a miracle? Or a largely predictable outcome? The answer depends on which of the many coincidences we consider.

### Serial: A Game of Numbers

Every analyst has their methods: take a poll, measure social media buzz, weigh various key factors. Rootclaim’s analysis of Serial: Who killed Hae Min Lee provides a good example of how the Rootclaim system uses hard numbers in order to “calculate reality” – to determine mathematically which hypothesis is the most likely.

Rootclaim recently took on one of the most controversial criminal convictions: that of Adnan Syed, sentenced to jail for murdering his ex-girlfriend Hae Min Lee. Syed’s conviction has been featured in the podcasts Serial and Undisclosed, and followers of the case have debated the minutiae on forums such as Reddit. Until now, discussion forums have focused on how a few particular pieces of evidence proved one hypothesis or another. Rootclaim has put together the first concerted effort to gather all the relevant information into one cohesive analysis.