GRE Data Interpretation Practice Questions with Solutions

Feeling lost in a sea of charts and graphs on the GRE? But what if we told you that Data Interpretation (DI) is within your grasp? Unlike traditional math problems, DI focuses on your ability to interpret information presented in charts, graphs, and tables. It’s all about deciphering details from the data itself.

This blog is your guide to acing the GRE Data Interpretation. We’ll share 10 practice problems that perfectly replicate the style and difficulty of the real GRE. Each question comes with a detailed solution, which helps you understand the logic behind the answer.

What is Data Interpretation on the GRE?

Data Interpretation (DI) is a specific question type you’ll come across in the quantitative reasoning section of the GRE. It assesses your ability to analyse and make sense of information presented in visual formats like charts, graphs, and tables. Unlike other quant problems that might focus on equations or specific formulas, DI is all about interpreting the data itself.

The GRE will present you with a single data set and then follow it up with three related questions. This data set could show trends over time, comparisons between different categories, or breakdowns of a whole into its parts. Your job is to decipher the information effectively. This might involve calculating values based on what’s shown, understanding the relationships between different data points, or making predictions based on the trends you see.

Importance of the GRE Data Interpretation

1. Sharpens analytical abilities

The core of DI is analysing complex data sets presented visually. You’ll need to identify patterns, trends, and relationships within the data. This hones your analytical thinking, a crucial skill for graduate programs that rely heavily on research and data-driven approaches.

2. Real-world relevance

Many graduate programs, especially in STEM fields, involve understanding and interpreting data in research papers, experiments, and real-world scenarios. By mastering DI, you can show your ability to analyse and utilise data effectively.

3. Quantitative Reasoning integration

The GRE incorporates DI questions within the quantitative reasoning section. While other problems might focus on GRE equations or GRE math formulas, DI brings a different dimension to quantitative reasoning. Mastering DI shows a well-rounded understanding of quantitative concepts and your ability to apply them in various data contexts.

4. Research and evaluation skills

Graduate programs heavily rely on research, and DI helps you evaluate research findings presented in a data-driven way. By effectively interpreting data sets, you can better assess the validity and significance of research conclusions.

5. Boosts GRE score

DI questions make up a significant portion of the quantitative reasoning section. Performing well in DI can significantly improve your total GRE score. Furthermore, it increases your chances of admission to competitive graduate programs.

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GRE Data Interpretation Practice Questions with Solutions

Answer the following questions (1–3) based on the information provided below.

Annual Percent Change in Dollar Amount of Sales at Five Retail Stores from 2006 to 2008

Source: ETS GRE

Question 1: If the dollar amount of sales at Store P was $800,000 for 2006, what was the dollar amount of sales at that store for 2008?

1. $727,200

2. $792,000

3. $800,000

4. $880,000

5. $968,000

Answer: Sales at Store P in 2006 were $800,000. They increased by 10% to $880,000 in 2007 and then decreased by 10% to $792,000 in 2008. It’s important to note that this final figure isn’t the same as the original amount because the percentage changes are applied to different base amounts ($800,000 for the increase and $880,000 for the decrease). So, the answer is (b) $792,000.

Question 2: At Store T, the dollar amount of sales for 2007 was what percent of the dollar amount of sales for 2008? Give your answer to the nearest 0.1 percent.

Answer: Let A represent the dollar amount of sales at Store T for 2007. An 8% decrease from 2007 to 2008 translates to 0.08A. Therefore, the sales in 2008 (A-0.08A) amount to 0.92A.

To find the percentage change in sales from 2007 to 2008, we divide A by 0.92A. This equals 1.0869565..., which is approximately 108.7% when expressed as a percentage and rounded to the nearest 0.1%. In conclusion, sales at Store T in 2007 were 108.7% of sales in 2008. So, the correct answer is 108.7%.

Question 3: Which of the following statements must be true? Indicate all such statements.

1. For 2008, the dollar amount of sales at Store R was greater than that at each of the other four stores.

2. The dollar amount of sales at Store S for 2008 was 22 percent less than that for 2006.

3. The dollar amount of sales at Store R for 2008 was more than 17 percent greater than that for 2006.

Answer: Since the table above only provides year-over-year percentage changes in sales, we cannot directly compare the actual dollar amounts for any store in 2008 or other years. This eliminates choice A, even though Store R shows the highest percentage increase from 2006 to 2008. The actual sales for Store R in 2008 could still be much lower than the others.

For choice B, the seemingly straightforward sum of 2% decreases (from 2006 to 2007 and 2007 to 2008) wouldn’t translate to a 22% decrease because the percentage changes are applied to different sales figures (bases). Let B represent the 2006 sales for Store S. In 2007, sales were 93% of B (0.93B), and in 2008, they were (0.85)(0.93)B, which is 0.7905B. This translates to an actual decrease of 100% - 79.05% = 20.95%, not 22%. Therefore, choice B is also eliminated.

However, choice C provides a definitive conclusion. If C represents Store R’s 2006 sales, then sales in 2007 were 1.05C and in 2008, (1.12)(1.05)C, which is 1.176C. This represents a 17.6% increase, exceeding the 17% threshold. Hence, only choice C holds true.

In conclusion, based on the provided information, only choice C is arguably accurate: the dollar amount of sales at Store R in 2008 was more than 17% greater than in 2006.

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5 Tips to Ace the GRE Data Interpretation

1. Know the data types

Get familiar with the various data presentations used in GRE DI, like bar graphs, line graphs, pie charts, tables, and scatter plots. Each format has its strengths for showing information, and understanding them helps you interpret the data quickly.

2. Brush up on math basics

GRE Data Interpretation questions often involve calculations using percentages, averages, ratios, and basic algebra. Brushing up on these concepts will ensure you can handle the necessary computations without getting stuck.

3. Extract, simplify, and solve

Don’t jump straight into calculations. Take time to extract key details from the data (numbers, trends, and relationships). Summarise the information in a way that makes sense to you, then proceed with calculations based on the question stem.

4. Question stem is key

Read the question carefully! Identify exactly what the question is asking about the data. This will guide your approach and prevent you from getting sidetracked by irrelevant information.

5. Practice makes perfect

There’s no substitute for practice. Do plenty of practice problems that cover different data types and question formats. This will improve your speed, accuracy, and test-taking stamina for the GRE exam.

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From the Desk of Yocket

Data Interpretation on the GRE assesses your ability to analyse and draw insights from complex information. This ability is essential for graduate programs, especially in research-oriented fields. While the GRE practice test itself doesn’t require advanced math knowledge, Data Interpretation challenges you to think critically about the information presented and apply basic mathematical concepts to reach conclusions. This prepares you for the kind of data analysis you’ll come across in your academic pursuits.

However, some might argue that the specific data sets presented on the GRE may not directly reflect the type of data you’ll encounter in every field. The focus on interpreting visuals can be seen as less relevant for disciplines that rely heavily on textual analysis or complex formulas. Nevertheless, the core skill of extracting meaning from data remains important, and the GRE’s Data Interpretation section provides a good baseline for assessing this ability. Incorporating Yocket Prep+ can further enhance your preparation by offering additional resources and practice materials tailored to your specific needs.