This report presents the prevalence of statistical terms and ideas in news stories. This involves (1) a judgment analysis of 160 articles and (2) a computer-match analysis of 899 articles. The judgment analysis of 160 articles involved 73 traits. Of these articles, 27% involve assembly in constructing categories or measures and 62% present associations that imply causation. Using judgment we find 42% influenced by confounding, 17% by assembly, 11% by bias and 9% by random effects. The computer-match of 899 number-based news articles calculated the prevalence of 231 statistical terms. In this set 19% use the word "significant" but only 3% use "statistically significant." Over 90% used comparisons, 74% used percent grammar, 67% used causal grammar, 61% used association grammar, 55% used chance, 32% used rates, 13% used percentage grammar and and 10% used confounding grammar.