Overview
Command of Evidence: Quantitative questions present a passage excerpt or a claim alongside an informational graphic — a bar graph, line graph, two-way table, scatter plot, or pie chart — and ask the student to select the data description that best completes or supports the claim. These questions are not math problems: no calculation is required. The skill being tested is the ability to read a graphic accurately, understand what the data shows, and match a specific data point or trend to the specific assertion made in the passage. Fewer than four of these questions typically appear on the exam, but they have a high student error rate due to graphic misreading.
Key Points
1. Graphic Types and What They Show
Each graphic type tests a slightly different reading skill:
| Graphic Type | What It Shows | Key Reading Skill |
|---|---|---|
| Bar graph | Comparison across categories at a point in time | Read bar heights accurately; note y-axis scale |
| Line graph | Trend over time for one or more variables | Identify direction of trend; note correct time range |
| Two-way table | Frequencies/counts at intersections of two categorical variables | Read both row AND column label before reading cell value |
| Scatter plot | Relationship/correlation between two continuous variables | Identify trend (positive/negative/none); note line of best fit |
| Pie chart | Proportional parts of a whole | Read percentage labels; note what the whole represents |
2. The Three-Step Hypothesis-Driven Method
Before looking at the graphic in detail, follow this sequence:
Step 1 — Rephrase the claim as a prediction: Read the claim or the blank in the passage and ask: “What kind of data would confirm this?” Convert the claim into a concrete prediction (e.g., “I am looking for a data point where Group A has a higher value than Group B in year 2022”).
Step 2 — Identify relevant graphic sections: Look only at the portion of the graphic that pertains to your prediction. Ignore irrelevant rows, columns, or time periods — they exist to generate wrong answer choices.
Step 3 — Evaluate each answer choice against the prediction: Ask for each choice: “Does this accurately describe what the graphic shows AND does it directly prove the prediction I derived from the claim?” Only one choice will pass both tests.
3. The Dual-Source Requirement
The correct answer must be supported by both the graphic and the passage text. This is the most important rule for this question type:
- A data description that is accurate according to the graph but does not match what the passage is claiming is a wrong answer
- A description that matches the passage’s topic but uses inaccurate data from the graphic is also wrong
- The intersection of “accurate data” + “relevant to the specific claim” = the correct answer
Example: If the passage claims “participants in the study showed improvement over time,” the correct answer must cite data from the graphic showing an upward trend for participants — not a flat trend, not a trend for a comparison group, and not a different time period.
4. Reading Bar Graphs Accurately
- Always read the y-axis scale before reading bar heights — the intervals may be in thousands, millions, or percentages
- For comparison questions, read the relevant bars in sequence and note which is taller/shorter
- Wrong answers frequently: swap which group is larger, use data from the wrong category, or confuse similar bar heights when the scale is compressed
5. Reading Two-Way Tables Accurately
Two-way tables cross-reference two categorical variables. The intersection cells are the data values.
- Before reading any cell, confirm you have the correct row (variable 1 category) AND the correct column (variable 2 category)
- The most common error: grabbing the right row but the wrong column (or vice versa)
- For “row total” or “column total” questions, do not confuse a row subtotal with the grand total
6. Reading Scatter Plots and Line Graphs
- Line graphs: Identify the time period the claim refers to, then trace the line for that period. Check if the trend is increasing, decreasing, or stable. Wrong answers describe the opposite trend or the trend from a different time range.
- Scatter plots: Identify the direction of the line of best fit (positive slope = positive correlation; negative slope = negative correlation). Note any outliers. Do not misread a slight positive correlation as “no correlation” or vice versa.
7. Unit Precision
Unit errors are the second-most-common wrong answer generator (after relevance errors):
- If the y-axis says “Number of participants (thousands),” a bar reaching “20” means 20,000, not 20
- If data is expressed as a percentage, wrong answers may describe it as a raw count (or the reverse)
- Read units in the axis label, the legend, and the graphic title — they can appear in any of these three places
Pitfalls and Common Mistakes
Pitfall 1: True Data, Wrong Claim (The #1 Trap) The most common wrong answer accurately describes real data from the graphic but does not address the specific claim in the passage. Students select it because “the number is in the graph” — but if that number does not support the passage’s specific assertion, it is wrong. Fix: After verifying that data is accurate, ask “Does this specific data point prove what the passage is claiming?” If not, eliminate it.
Pitfall 2: Correct Row, Wrong Column (Table Intersection Error) In two-way tables, students often identify the right row label but then read the value from an adjacent (wrong) column — selecting a plausible-looking number that is real but from the wrong intersection. Fix: Before reading a cell value, physically confirm both labels — read the row label AND the column label for that intersection.
Pitfall 3: Unit Confusion (Thousands vs. Millions, Percent vs. Count) Wrong answer choices frequently express a data point in the wrong unit (e.g., stating a raw number when the graph shows thousands, or stating a percentage when the data is a raw count). Fix: Read the y-axis label before reading any data values. Note the unit and apply it to every answer choice you evaluate.
Pitfall 4: Wrong Time Period or Category Line graphs covering multiple years, or bar graphs with multiple categories, generate wrong answers by using accurate data from the wrong year or the wrong group — a real number, just from the wrong location in the graphic. Fix: When the claim specifies a time period or category, anchor your eye to that specific portion of the graphic first before comparing bar heights or reading trend lines.
Pitfall 5: Opposite Trend For trend questions (line graphs, scatter plots), a classic wrong answer describes the opposite trend — increasing instead of decreasing, or a negative correlation instead of a positive one. Fix: Before reading answer choices, state the trend to yourself in plain language: “The line goes up from 2018 to 2022.” Then eliminate any choice that contradicts this.
Related Entries
- Command_Evidence_Textual
- Central_Ideas_Details
- Inferences
- Paired_Passage_Questions
- Data_Distribution_Graphs
Quick Reference Card
| Graphic Type | Most Common Trap | Prevention |
|---|---|---|
| Bar graph | Wrong category / compressed scale misread | Read y-axis scale before reading bars |
| Line graph | Wrong time period / opposite trend | Anchor to correct time range first |
| Two-way table | Correct row, wrong column (or vice versa) | Confirm both row AND column labels before reading cell |
| Scatter plot | Misread correlation direction / confuse outliers for trend | Identify line of best fit direction first |
| Pie chart | Confuse sector percentage with raw count | Check what the whole represents and the unit type |
| Step | Quantitative Evidence Process |
|---|---|
| 1 | Read the claim/blank → rephrase as a concrete data prediction |
| 2 | Read graphic title, axis labels, legend, and units BEFORE looking at data |
| 3 | Identify the specific graphic section relevant to your prediction |
| 4 | For each answer choice: (a) Is the data accurate? (b) Does it prove the specific claim? |
| 5 | Select the choice that passes BOTH tests; eliminate choices that pass only one |