This is a great Multi-Source Reasoning question that tests your ability to interpret graphs and apply logical reasoning. Let me walk you through how to approach both parts systematically.
Question 1: Finding the Peak Expansion Coverage YearLet's think about what the question is really asking. You're told that expansion stories "increase steeply and steadily after a recession ends" and "decrease sharply when a recession begins."
Here's what you need to see: If expansion stories build up during good times and crash during recessions, then they'd be highest right
before the next recession starts.
Step 1: Look at the graph and identify the longest period without a grey shaded area (recession).
Step 2: Notice the expansion from 1991 (when a recession ends) to 2001 (when the next one begins). This is roughly 10 years - by far the longest expansion period shown.
Step 3: Since expansion stories accumulate throughout this period and would peak just before the 2001 recession, the answer is
2000.
Question 2: Understanding Story Composition (1975-1976)This one requires some careful logical reasoning. Notice how during 1975-1976 (a recession period), the Finance Times line is
higher than Metro Journal's line on the graph.
Here's the key insight: The graph shows only recession-focused articles. If Finance Times had:
- More recession articles (as shown on the graph)
- But fewer total articles overall (as stated in the question)
Then mathematically, Finance Times must have had
significantly fewer expansion articles!
Think of it this way:
\(Total = Recession + Expansion\)
If \(FT_{total} < MJ_{total}\) and \(FT_{recession} > MJ_{recession}\)
Then \(FT_{expansion}\) must be much less than \(MJ_{expansion}\)
The answer is
primarily about expansions.
You can check out the
step-by-step solution on Neuron by e-GMAT to master the systematic framework for handling inverse relationships in data interpretation questions. You can also explore other GMAT official questions with detailed solutions on Neuron for structured practice
here, including advanced techniques for quickly identifying patterns in cyclical data and alternative approaches to verify your answers.