Caselets in Data Interpretation are paragraph-based questions where data is presented in story format instead of charts or tables. These questions test your ability to extract numerical information from text and perform calculations. In SSC CGL, caselets typically appear as 3-5 questions based on one paragraph containing business scenarios, financial data, or statistical information. Key characteristics of caselets include mixed data presentation, multiple calculation steps, and real-world contexts like company profits, population studies, or survey results. The data is embedded within sentences, requiring careful reading to identify relevant numbers and relationships.
Common caselet patterns in SSC CGL include percentage calculations (profit/loss, growth rates), ratio and proportion problems, average and percentage combination, and simple interest/compound interest scenarios. Questions often involve finding missing values, comparing different entities, or calculating derived metrics. Formulas frequently used:
Percentage increase/decrease = (New Value - Old Value)/Old Value × 100 Average = Sum of all values/Number of values
Ratio calculation = Part/Whole × 100 Profit percentage = (Selling Price - Cost Price)/Cost Price × 100
Create a data extraction table while reading. Write down all numerical values with their labels in tabular format. This prevents re-reading and saves 30-40 seconds per question.
Extract data 2022 revenue = 50 lakhs 2023 revenue = 50 + 20% of 50 = 50 + 10 = 60 lakhs 2023 expenses = 60% of 60 = 36 lakhs 2023 profit = 16 lakhs
Verify (Revenue - Expenses = Profit) 60 - 36 = 24 lakhs (but profit given as 16 lakhs, so expenses = 60 - 16 = 44 lakhs)
Calculate expense percentage of 2022 revenue Expense percentage = (44/50) × 100 = 88% Another useful trick: Use approximation for quick elimination. If exact calculation seems time-consuming, round numbers to nearest 5 or 10 for faster computation, then match with closest option.
include misidentifying which year/entity the question refers to, mixing up base values for percentage calculations, and not verifying if calculated values make logical sense. Always cross-check your final answer against the given constraints in the paragraph.
25graded MCQs · easy to hard · full solution & trap analysis · showing 20 of 25
Study the following table showing quarterly sales data (in lakhs ₹) for a retail company across four regions and answer the questions.
| Region | Q1 | Q2 | Q3 | Q4 |
|---|---|---|---|---|
| North | 120 | 150 | 180 | 210 |
| South | 100 | 120 | 140 | 160 |
| East | 80 | 100 | 120 | 140 |
| West | 140 | 160 | 180 | 200 |
Study the following table and answer the questions. The table below shows the monthly sales (in lakhs ₹) of five product categories across a retail chain for the year 2023.
| Month | Electronics | Clothing | Home & Kitchen | Sports | Books |
|---|---|---|---|---|---|
| Jan | 45 | 32 | 28 | 18 | 12 |
| Feb | 48 | 35 | 30 | 20 | 14 |
| Mar | 50 | 38 | 32 | 22 | 16 |
| Apr | 52 | 40 | 35 | 25 | 18 |
| May | 55 | 42 | 38 | 28 | 20 |
| Jun | 60 | 45 | 40 | 30 | 22 |
Study the following table and answer the questions. The table below shows the quarterly sales (in lakhs ₹) of five product categories for a retail company in the financial year 2023-24.
| Product Category | Q1 | Q2 | Q3 | Q4 |
|---|---|---|---|---|
| Electronics | 120 | 150 | 180 | 210 |
| Clothing | 80 | 100 | 120 | 140 |
| Home & Kitchen | 60 | 75 | 90 | 105 |
| Sports & Outdoors | 40 | 50 | 60 | 70 |
| Books & Media | 20 | 25 | 30 | 35 |
Study the following table carefully and answer the questions based on the data provided. The table below shows the sales performance (in lakhs of rupees) of five regional branches of TechCorp Industries across four quarters of a financial year.
| Branch | Q1 | Q2 | Q3 | Q4 |
|---|---|---|---|---|
| North | 120 | 150 | 180 | 210 |
| South | 100 | 110 | 121 | 133 |
| East | 80 | 96 | 115 | 138 |
| West | 140 | 140 | 140 | 140 |
| Central | 160 | 176 | 194 | 212 |
Study the following table carefully and answer the questions based on the data provided. A manufacturing company tracks quarterly production and sales data across four product lines (A, B, C, D) for the financial year 2023-24.
| Product | Q1 Production (units) | Q1 Sales (units) | Q2 Production (units) | Q2 Sales (units) | Q3 Production (units) | Q3 Sales (units) | Q4 Production (units) | Q4 Sales (units) |
|---|---|---|---|---|---|---|---|---|
| A | 5000 | 4500 | 5500 | 5200 | 6000 | 5800 | 6500 | 6200 |
| B | 4000 | 3600 | 4500 | 4200 | 5000 | 4800 | 5500 | 5300 |
| C | 3000 | 2700 | 3500 | 3150 | 4000 | 3800 | 4500 | 4050 |
| D | 2000 | 1800 | 2500 | 2250 | 3000 | 2700 | 3500 | 3150 |
Note: All figures are in units. Sales figures represent actual units sold in each quarter.
Study the following table carefully and answer the questions based on the data provided. The table below shows the production and sales figures (in units) of five manufacturing units (A, B, C, D, E) across four quarters of a financial year, along with the cost price and selling price per unit.
| Unit | Q1 Production | Q1 Sales | Q2 Production | Q2 Sales | Q3 Production | Q3 Sales | Q4 Production | Q4 Sales | Cost Price (₹) | Selling Price (₹) |
|---|---|---|---|---|---|---|---|---|---|---|
| A | 1200 | 1100 | 1400 | 1350 | 1600 | 1550 | 1800 | 1750 | 500 | 750 |
| B | 1500 | 1400 | 1600 | 1500 | 1700 | 1650 | 1900 | 1850 | 600 | 900 |
| C | 800 | 750 | 900 | 850 | 1000 | 950 | 1100 | 1050 | 400 | 650 |
| D | 2000 | 1900 | 2100 | 2000 | 2200 | 2100 | 2300 | 2200 | 550 | 850 |
| E | 1000 | 950 | 1100 | 1050 | 1200 | 1150 | 1300 | 1250 | 480 | 720 |
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