XAT Data Interpretation: Graphs, charts, tables requiring insightful analysis Notes: Chapter-wise Weightage and Solved Questions

XAT Data Interpretation: Graphs, charts, tables requiring insightful analysis: 4 chapters, 0 practice questions and one solved question from each chapter.

Data Interpretation: Graphs, charts, tables requiring insightful analysis Chapter Matrix

Chapter	PYQs	Share of unit PYQs	Practice questions
Graphs, Scatter Plots and Trend Analysis	0	0%	0
Hierarchical Charts and Business Decision Tables	0	0%	0
Statistical Measures and Distribution Analysis	0	0%	0
Tables, Missing Data and Logical Reconstruction	0	0%	0

One Solved Question from Each Data Interpretation: Graphs, charts, tables requiring insightful analysis Chapter

Question 1 · Quantitative Aptitude and Data Interpretation (QA & DI) MCQ

Refer to the hypothetical dataset describing 12 regions. Graph A plots "Per Capita Healthcare Spend ( $) " o n X - a x i s v s " L i f e E x p ec t an cy (Y e a r s) " o nY - a x i s . G r a p h B pl o t s " P er C a p i t a H e a l t h c a r e S p e n d ($ )" on X-axis vs "Patient Satisfaction Score (0-10)" on Y-axis.

Observations:

In Graph A, points form a steep positive curve for spends up to $3, 000, t h e n f l a tt e n co m pl e t e l y in t o ah or i z o n t a l l in e f or s p e n d s >$ 3,000.
In Graph B, points show a steady linear upward trend across the entire spend range ( $500 t o$ 8,000).

Based ONLY on these graphs, which inference is MOST valid?

A.
Increasing healthcare spend beyond $3,000 yields no additional benefit to patients.
B.
Life expectancy is biologically capped, whereas patient satisfaction is subjective and unbounded by physiological limits.
C.
For regions spending > $3,000, marginal gains in life expectancy are negligible, but marginal gains in satisfaction persist.
D.
Regions with highest satisfaction scores necessarily have the highest life expectancy.

Correct Answer:

Step-by-Step Solution

Key idea: This is a multi-graph synthesis question. It tests the ability to reconcile conflicting/divergent trends across two related visualizations and avoid over-generalization.

Step 1: Interpret Graph A (Life Expectancy).

Shape: Logarithmic/Saturation. Steep rise then plateau.

Meaning: Marginal utility of spend on LE drops to zero after $3k.

Step 2: Interpret Graph B (Satisfaction).

Shape: Linear. Constant positive slope.

Meaning: Marginal utility of spend on Sat remains constant/positive even at high spend.

Step 3: Synthesize.

At spend > $3 k :$ \Delta LE \approx 0 $, b u t$ \Delta Sat > 0$.

This directly supports Option C.

Step 4: Reject distractors.

A: False. Says "no additional benefit." Ignores Satisfaction benefit shown in Graph B.

B: Invalid. Introduces external biological/psychological theory not present in data. Data shows correlation, not cause/mechanism.

D: False. Correlation between Sat and LE is not established. High spend regions have high Sat but flat LE. They might have same LE as mid-spend regions.

Answer: C

chapter

XAT Data Interpretation: Graphs, charts, tables requiring insightful analysis Notes: Chapter-wise Weightage and Solved Questions

XAT Data Interpretation: Graphs, charts, tables requiring insightful analysis: 4 chapters, 0 practice questions and one solved question from each chapter.

A question from this chapter

Question 1

Refer to the hypothetical dataset describing 12 regions. Graph A plots "Per Capita Healthcare Spend () " o n X - a x i s v s " L i f e E x p ec t an cy (Y e a r s) " o nY - a x i s . G r a p h B pl o t s " P er C a p i t a H e a l t h c a r e S p e n d ()" on X-axis vs "Patient Satisfaction Score (0-10)" on Y-axis. Observations: In Graph A, points form a steep positive curve for spends up to 3, 000, t h e n f l a tt e n co m pl e t e l y in t o ah or i z o n t a l l in e f or s p e n d s > 3,000. In Graph B, points show a steady linear upward trend across the entire spend range (500 t o 8,000). Based ONLY on these graphs, which inference is MOST valid?

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