Goodness-of-fit statistics

Goodness-of-fit statistics are measures used to assess how well a statistical model represents observed data. They help determine if a model accurately captures the underlying patterns in the data. By comparing the expected outcomes from the model with the actual data, these statistics reveal how closely the model fits. A good fit means the model explains the data well, while a poor fit indicates discrepancies. Common examples include the Chi-square statistic and R-squared value, which help researchers evaluate their models and make informed decisions based on their analysis.