These data usually accompany contemporary political or election stories, forecasting outcomes or public sentiment on issues ranging from city council elections to school bond issues. Check here for some examples of public opinion polling . Typically, this may involve analysis of readership studies, TV ratings or of actual incident counting in programs or articles. Here's a content analysis of 1950's radio news to provide a contrast to the kinds of stories common today. In short, there are many instances where numeric data must be organized and summarized to see patterns and answer questions.
Reduction implies that the data are summarized using descriptive statistics.
Averages, highs and lows, median points and variation are such summary indicators. Testing implies that data are compared to see if there are major differences between groups. This often involves statistical inference or projecting from a sample to the population at large. There are many details involved here that do not concern this course, but testing is, nevertheless, one of the major reasons journalists want to capture data for analysis. Here's an example of many comparisons for minority journalists - but no real testing for chance differences.