We observed what can go wrong when journalists who lack an understanding of statistical inference make claims about data in How Mail Today got its analysis of communal violence exactly wrong. This tendency became clear once again from an Apr 26 article in The Hindu titled Gujarat behind West Bengal in new factory jobs, as the following analysis shows:

Guest post by Philip K. Oldenburg, Research Scholar, South Asia Institute, Columbia University 

Perhaps the most common error the media make when presenting data is to use the “absolute” numbers on their own, rather than adjusting them appropriately. For example, growth in income should always be “real,” adjusted to eliminate the effect of inflation. In a piece headlined “Gujarat behind West Bengal in new factory jobs; National Sample Survey data poses a challenge to ‘Gujarat growth model’,” published in The Hindu recently (April 26, 2014), we find a graph showing that there were 24 lakh jobs created in the manufacturing sector between 2004 and 2011 in West Bengal, versus 14.9 lakh jobs in Gujarat — some 60% more, making the state a “distant second.”

If one adjusts the figures to take into account the differing populations of the various states, the graph would be much less dramatic, and the ranking changes (excluding states with negative job creation):

Jobs created per 10,000 population

West Bengal is now only 8.5% “better” than Gujarat. (Ideally, one would “normalize” the absolute numbers in this case by using some other denominator that would adjust for size of the state: perhaps its adult worker population, or something else.) That adjustment makes the analysis in the rest of the report irrelevant, in my opinion.

In the best of all possible worlds, any reporter assigned to do a story that rests on quantitative data should have had at least a course in elementary statistics, and every editor (equipped similarly) would catch errors in data presentation and analysis with about the same failure rate as now exists for typographical errors.