College Board Blue Book | Test 7 | Module 2 Hard | Domain 1 | Graphs

By Mr. Osama Ahmad February 17, 2025 12 min read

Ace Digital SAT Data Questions: Expert Guide to Reading & Inference (Bluebook Test 7, Module 2)

Ace Digital SAT Data Questions: Your Expert Guide (Test 7, Module 2)

Hey everyone! Mr. O here from The Test Advantage, back to help you crush the Digital SAT. 👋

Feeling tripped up by those Digital SAT Reading questions with graphs and data? You're not alone! They can be tough, especially in the harder Module 2 sections. Today, we’ll tackle two tricky ones (Questions 10 & 11) from the official College Board Bluebook app: Test 7, Module 2 (Hard).

Let's break them down step-by-step so you can confidently handle data interpretation and inference questions. Getting these right is key to helping you improve your Digital SAT score!

Watch the video walkthrough for an even deeper dive!

Approach for Hard Module 2 Reading Questions

First things first: when you hit Module 2, especially the hard version, slow down! Every word in the text matters. Don't just glance at the graph; understand the story the text is telling before you try to connect it to the data. This approach is vital for many digital SAT questions.

Question 10 Walkthrough

In a study of urban physical expansion, Berta Malmer et al. conducted a meta-analysis of more than 300 cities worldwide to determine whether urban land expansion (ULE) was more strongly influenced by urban population growth or by growth in gross domestic product (GDP) per capita, a measure of economic activity. Because efficient national government is necessary to provide urban services and infrastructure that attract economic investment, Malmer et al. propose that, absent other factors, the importance of GDP per capita growth to ULE would likely increase relative to the importance of population growth as governments become more efficient. If true, this suggests the possibility that _______.

Graph comparing influence of population growth and GDP growth on Urban Land Expansion in two regions over two time periods.

Which choice most effectively uses data from the graph to complete the statement?

(A) national governments of countries in Region 1 experienced declines in efficiency in the period from 2000 to 2014, relative to the period from 1970 to 2000.

(B) countries in Region 1 experienced a slower rate of economic growth in the period from 2000 to 2014 than countries in Region 2 did, despite increasing national government efficiency in Region 1.

(C) national governments of most countries in Region 2 became more efficient in the period from 2000 to 2014 than they had been in the period from 1970 to 2000, but those of several countries in this region did not.

(D) national governments of countries in Region 1 and in Region 2 generally became more efficient in the period from 2000 to 2014 than they had been in the period from 1970 to 2000, but at different rates.

Breaking Down the Logic:

The question asks us to finish the sentence using the graph data.
The text connects: Urban Land Expansion (ULE), Population Growth (PG), Economic Activity (GDP), and Government Efficiency (govt efficiency).
The Core Idea: More efficient government means GDP growth becomes *more* important for city expansion (ULE) compared to population growth. Less efficient government means GDP growth becomes *less* important.

We need to find the answer that shows this relationship playing out in the graph.

Looking at the Graph:

The graph shows how much ULE was influenced ("percentage attribution") by Population Growth (gray bars) vs. GDP Growth (black bars).
Region 1: From 1970-2000 to 2000-2014, PG's influence *went up* (gray bar got taller), and GDP's influence *went down* (black bar got shorter). Based on the text's logic, this points to government efficiency *decreasing*.
Region 2: From 1970-2000 to 2000-2014, PG's influence *went down* (gray bar got shorter), and GDP's influence *went way up* (black bar got much taller). This suggests government efficiency *increasing*.

Checking the Answers:

(A) national governments of countries in Region 1 experienced declines in efficiency in the period from 2000 to 2014, relative to the period from 1970 to 2000.
✅ Correct! This matches our graph analysis for Region 1 perfectly. The decreasing influence of GDP suggests declining efficiency.
(B) Countries in Region 1 experienced a slower rate of economic growth... despite increasing national government efficiency in Region 1.
❌ Incorrect. The graph shows GDP's *influence* decreased, not necessarily the *rate* of economic growth itself. Plus, it incorrectly states efficiency *increased* in Region 1.
(C) ...governments of most countries in Region 2 became more efficient... but those of several countries... did not.
❌ Incorrect. The graph supports increased efficiency in Region 2 overall, but we have *no data* about specific countries *within* the region. This goes beyond what the graph tells us – a common trap in SAT test prep!
(D) ...governments of countries in Region 1 and in Region 2 generally became more efficient...
❌ Incorrect. This gets Region 1 wrong. Our analysis showed efficiency likely *decreased* there.

The best answer is (A).

Winning Strategy: Decode the Relationships

For graph questions, always figure out the 'if-then' relationship described in the text first. How do the pieces connect? Here, it was "If government efficiency goes up, then GDP influence goes up." Apply that logic to the visual data. This strategy helps you tackle tough digital SAT data questions.

Question 11 Walkthrough

A student is researching the Chinese government’s 1992 shift to a market economy that emphasizes trade liberalization (making trade easier). One means of trade liberalization involves expanding from ordinary imports into an emphasis on processing imports, which have two types: processing with assembly (in which a firm obtains raw materials from a foreign trading partner without payment and sells the final goods to that partner, charging for assembly) and processing with inputs (in which a firm expends capital to buy raw materials from a trading partner, processes them into final goods, and sells those goods to whichever trading partner it chooses). The student asserts that while initial efforts at trade liberalization were shaped by Chinese firms’ limited capital, this situation resolved during the 2000s.

Graph showing China's imports by type (Ordinary, Processing with Assembly, Processing with Inputs) from 2000 to 2006.

Which choice best describes data from the graph that support the student's assertion?

(A) Processing imports with inputs were greater than both ordinary imports and processing imports with assembly in 2006.

(B) From 2000 to 2006, processing imports with inputs rose much more sharply than processing imports with assembly did.

(C) From 2000 to 2006, neither processing imports with inputs nor processing imports with assembly were greater than ordinary imports.

(D) Processing imports with assembly were greater in 2006 than processing imports with inputs in 2000.

Understanding the Student's Point:

The student claims two things:
1. At first, Chinese companies didn't have much money (limited capital), which affected how they traded.
2. This lack of money situation got resolved (they got more capital) in the 2000s.
Let's simplify the import types:
- Processing with assembly (PwA): Like assembling a kit for someone else. You don't pay for the parts (raw materials). Good if you're low on cash.
- Processing with inputs (PwI): You buy the parts (raw materials) yourself, then make and sell the final product. Requires money upfront (capital).

The Logical Link: If firms started with little money, they'd prefer PwA (no upfront cost). If they later *got* money, they could switch to PwI (buying their own materials). So, the student's assertion suggests a shift *away from* PwA and *towards* PwI during the 2000s.

Reading the Graph (2000-2006):

Let's focus on the two processing types: PwA (light gray line/area) and PwI (black line/area).
In 2000: PwA is clearly higher than PwI. This fits the "limited capital" idea.
From 2000 to 2006: The PwI line shoots up dramatically. The PwA line stays relatively flat or even dips slightly.
By 2006: PwI is *much* higher than PwA.

This visual trend strongly supports the student's assertion: the rise of PwI suggests companies gained the capital needed to buy their own inputs, resolving the earlier limitation.

Analyzing the Answer Choices:

(A) Processing imports with inputs were greater than both ordinary imports and processing imports with assembly in 2006.
❌ Incorrect. While this statement might be true from the graph, it's just a snapshot of 2006. It doesn't show the *change over time* that proves the student's point about capital being resolved. We need evidence of the *shift*.
(B) From 2000 to 2006, processing imports with inputs rose much more sharply than processing imports with assembly did.
✅ Correct! This captures the *dynamic shift* shown in the graph. The rapid growth of PwI compared to PwA directly supports the idea that firms gained capital and moved towards the model requiring upfront investment. This is exactly what we needed!
(C) From 2000 to 2006, neither processing imports with inputs nor processing imports with assembly were greater than ordinary imports.
❌ Incorrect. Firstly, this seems factually wrong based on the graph (PwI surpasses Ordinary Imports later). Secondly, comparing with ordinary imports isn't relevant to the student's specific point about the shift *between the two processing types* due to capital changes.
(D) Processing imports with assembly were greater in 2006 than processing imports with inputs in 2000.
❌ Incorrect. This is factually wrong according to the graph. PwI in 2006 is vastly larger than PwA in 2000 (and even PwA in 2006).

The best answer is (B).

Winning Strategy: Nail the Assertion First

Before you even glance at the graph details, fully unpack the student's claim. What exactly are they arguing? What kind of *change* or *comparison* would support their point? Here, it was about a *shift* caused by a *change* in finances. Finding the graph data showing that shift is key. Think of the text as your SAT test study guide for interpreting the visual.

Great job working through these tough questions! 👍 Mastering data interpretation is crucial for hitting your target score on the Digital SAT.

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