11: One small correction

The method I showed you on the last page was not quite right. For reasons that are difficult
to explain without a degree in statistics, you need to SQUARE the deviation
before dividing by the expected value. So we have the following sequence:

    Determine what you “expected” to see.

    Find out the difference between the
    observed and expected values (subtract)

    Square those differences

    Find out how big those squared differences
    are compared to what you expected (divide)

    Add it all up.

chi-square = sigma ( (o-e)^2) / e )

Place mouse on picture for more explanation

If the final chi-square is a big number, would this make you think that the data fit the model, or don’t fit the model?