GMAT (Graduate Management Admission Test) Data Insights: Data Analysis & Integrated Reasoning Syllabus

Data Insights: Data Analysis & Integrated Reasoning syllabus — full chapter and topic list

Expand any chapter to see its topics and sub-topics. This is the whole examinable outline for Data Insights: Data Analysis & Integrated Reasoning in GMAT (Graduate Management Admission Test), not a summary of it.

1. 1

   Table Analysis

   4 topics

   • Sorting and filtering sortable tables
   • Reading multi-column data efficiently
   • True/false and yes/no statement evaluation
   • Computing statistics from table data
2. 2

   Graphics Interpretation

   4 topics

   • Reading bar, line, and scatter plots
     • Identifying trends and correlations
     • Reading axes, scales, and legends
   • Interpreting pie charts and segmented graphics
   • Completing drop-down inference statements
   • Extrapolation and estimation from graphs
3. 3

   Multi-Source Reasoning

   4 topics

   • Synthesizing information across tabs
   • Locating relevant data among distractors
   • Cross-referencing text, tables, and charts
   • Inference and computation across sources
4. 4

   Two-Part Analysis

   4 topics

   • Quantitative two-part problems
   • Verbal/logical two-part problems
   • Handling interdependent answer columns
   • Tradeoff and optimization scenarios
5. 5

   Data Literacy & Quantitative Interpretation

   4 topics

   • Working with the on-screen calculator effectively
   • Units, rates, and percent reasoning in data context
   • Distinguishing correlation from causation in data
   • Estimation and sanity-checking results

Data Insights: Data Analysis & Integrated Reasoning flashcards for GMAT (Graduate Management Admission Test)

22 of 50 cards from the Data Insights: Data Analysis & Integrated Reasoning deck — real questions with worked answers.

1. On the GMAT Data Insights Table Analysis question type, what does each table provide and what is the standard answer format?

   It provides a sortable table of data (rows of records, columns of attributes) that you can sort by any column. You answer three statements, each as a binary choice such as Yes/No, True/False, or Would-help/Would-not-help, and you must get all three correct for credit.

2. What is the single most efficient first step when a GMAT sortable table question asks about extremes (highest, lowest, top 3, median)?

   Sort the table by the relevant column before reading. Sorting reorders the rows so extremes and rank-based answers can be read directly instead of scanning all rows.

3. When reading a multi-column data table efficiently, what should you do BEFORE looking at the answer statements?

   Read the column headers and their units, and note the source/intro text. Understanding what each column represents (and its units) prevents misreading values when you return to evaluate statements.

4. In Table Analysis, how should you treat the three statements relative to each other?

   Treat each statement as completely independent. The truth of one statement gives no information about the others, so evaluate each separately against the data.

5. For a True/False or Yes/No statement evaluation, what makes a statement FALSE?

   A statement is false if even one counterexample exists or any part of it fails. To be true it must hold completely; a single violating row makes a 'for all' claim false.

6. How do you decide between 'True' and 'Cannot be determined' for a table statement?

   Mark it true only if the data fully supports it. If the table lacks the information needed (e.g., asks about a value or relationship not given), the statement is not supported, so it is false/No rather than assumed true.

7. What is the formula for the arithmetic mean (average) you must compute from table data?

   Mean = (sum of all values) / (number of values).

8. How do you find the median of a column of data in a table?

   Sort the values in order. If n is odd, the median is the middle value (position (n+1)/2). If n is even, the median is the average of the two middle values.

9. What is the range of a data set and how is it computed from a sorted table column?

   Range = maximum value − minimum value. After sorting the column, subtract the first (smallest) value from the last (largest) value.

10. In data context, how do you compute a percent change between an old and new value?

    Percent change = (new value − old value) / old value × 100%. A positive result is an increase, negative is a decrease.

11. How do you compute what percent value A is OF value B from table data?

    Percent = (A / B) × 100%. 'A is what percent of B' always divides by the base B (the value following 'of').

12. On a bar chart in Graphics Interpretation, how do you read a value accurately?

    Trace the top of the bar horizontally to the value axis and read the gridline. Note the axis scale and units; estimate between gridlines proportionally if the bar ends between marks.

13. What does the slope of a line on a line graph represent, and how is it interpreted?

    Slope = rise/run = change in the y-variable per unit change in the x-variable. A steeper slope means a faster rate of change; a flat line means no change; a negative slope means a decreasing quantity.

14. On a scatter plot, what does a positive vs. negative correlation look like?

    Positive correlation: points trend upward left-to-right (as x increases, y increases). Negative correlation: points trend downward left-to-right (as x increases, y decreases). No pattern means little or no correlation.

15. On a scatter plot, how do you identify an outlier?

    An outlier is a point that lies far from the general cluster or trend line of the other points, deviating noticeably in the x and/or y direction.

16. In a pie chart, how do you convert a slice's percentage into an actual quantity?

    Multiply the slice's percentage by the total represented by the whole pie: quantity = (slice percent) × total. The full circle (360°) equals 100% of the total.

17. In a pie chart, how many degrees correspond to a given percentage of the whole?

    Degrees = (percentage/100) × 360. For example, 25% = 90°, 50% = 180%, and 1% = 3.6°.

18. What is the structure of a Graphics Interpretation question and how do you answer it?

    You are given a graph/chart plus two fill-in-the-blank statements, each completed by selecting from a drop-down menu of options. You must choose the correct option for each blank based on the graphic.

19. When completing a drop-down inference statement, what is the recommended approach to the options?

    Read the full sentence first to know what is being asked, then check the drop-down choices. Compare candidate answers against the graphic and eliminate options the data contradicts, rather than guessing before reading them.

20. What does extrapolation from a graph mean, and what is its key caution?

    Extrapolation is extending a trend beyond the plotted data range to estimate values not shown. The caution: it assumes the trend continues, which may not hold, so treat extrapolated values as estimates with uncertainty.

21. What is interpolation, and when is it more reliable than extrapolation?

    Interpolation estimates a value BETWEEN known data points (within the plotted range). It is generally more reliable than extrapolation because you are estimating inside the observed pattern rather than beyond it.

22. What is the structure of a Multi-Source Reasoning (MSR) question set on the GMAT?

    Two or three tabbed pages present related information (text, tables, charts, emails, etc.). Several questions then require you to combine information across the tabs to answer; you switch between tabs as needed.

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