Profile
Settings
Refer your friends
Sign out
Introduction
Data interpretation and sufficiency are two important topics on the GMAT. This blog post will teach you how to analyze data and answer questions related to it. First, we will discuss what data interpretation is and why it is important. Then, we will go over the different types of data sets you may encounter on the GMAT. Finally, we will teach you how to answer questions related to data interpretation and sufficiency. Follow these tips, and you’ll be able to conquer the GMAT!
What Is Data Interpretation?
Data interpretation is the process of analyzing data to answer questions. The data can be numerical or textual, and the questions can be about the data itself or something else. Data interpretation is an essential skill for business and academic contexts, as well as everyday life.
What Is Sufficiency?
Sufficiency is a property of data that ensures that the data can answer the question. Data is sufficient if it is enough to answer the question. If more data is needed, then the data is not sufficient.
How to Analyze Data?
There are two steps in analyzing data: (i) understanding the data and (ii) determining whether the data is sufficient.
Understanding Data
To understand a data set, one must read it carefully and make sure that each piece of information can be clearly understood; otherwise, there may be no way to answer questions about the data. For example: consider this sentence “The income of two people in a family is $50,000.”
The first thing we need to determine the data is the units of measurement. The income is given in dollars, so we know that the unit of measurement is dollars. Next, we need to determine what the data represents. In this sentence, the data represents the income of two people in a family. Finally, we need to determine the meaning of the data. In this sentence, the data means that the income of two people in a family is $50,000 each.
Determining Sufficiency
Once we understand the data, we can determine whether it is sufficient to answer the question. For example: consider this question “How much money do two people in a family make?” We know that the data is not sufficient because we need to know how much each person makes.
How to Answer Questions with Data Interpretation and Sufficiency
There are three steps in answering questions with data interpretation and sufficiency:
(i) understanding the question,
(ii) finding the answer in the data, and
(iii) determining whether the answer is sufficient.
Understanding Questions
To understand a question, we need to determine what it means. For example: consider this question “What is your favorite color?” We know that the question is asking for our favorite color; so if we are asked this question in an interview, then our answer must be color.
Finding Answers in Data
Once we understand the question, we can use data interpretation to find the answer in the data. For example: consider this dataset “Blue, Red” and the question “What is your favorite color?” We know that the first word in each entry of the data is a color, so we can use data interpretation to find the answer in the dataset.
Determining Sufficiency of Answers
Finally, once we find an answer in the data, we need to determine whether it is sufficient. For example: consider this question “How much money do two people make?” If our answer is “Blue, Red” then the answer is not sufficient because we need to know how much each person makes.
Conclusion
Let’s explore how data interpretation and sufficiency are two important concepts to consider when using statistical evidence. A good way to think about these principles is by asking yourself the following questions, “If I have a sample size of 10 people, am I able to make conclusions for all humans? Or does my conclusion only apply to those in the study? And if so, can this be extrapolated outwards with confidence?” If you want help analyzing your data or just need someone who understands statistics on your team that can answer any question you may have then please contact us!
