SIGma-X GFE Mocks

Truly Adaptive

Rather than using a simple question-based adaptive engine, SIGma-X mocks use a sophisticated adaptive engine based on Item Response Theory (IRT) to ensure that the difficulty level of questions served truly adapts to your actual ability.

Large Pool
of Questions

Each test draws from a question pool that contains 3X as many questions as in competing mocks so you can be certain that no matter what your ability, the test will serve questions of appropriate difficulty level.

5-Difficulty

levels

While most mock tests serve questions from three question banks - Easy, Medium, or Hard, SIGma-X mocks' question picking engine picks questions from 5 different question banks - the result - a more precise estimate of your ability.

Block

Question-level

adaptability

Our advanced question picker dynamically adjusts the complexity of next question by analyzing not only your most recent response, but also how you have answered questions till that point. This method enables an exceptionally accurate assessment of your ability.

Unparalleled Insights

Sigma-X mocks provide meaningful, data-driven insights that tell you how you can achieve your target GMAT score.

Get Target Sectional Scores

Target Sectional Scores
GFE mocks not only give you your current sectional scores, they also give you the target sectional scores that you need to achieve your target GFE score. This kind of granularity in feedback is game-changing.

Clear Roadmap
Instead of sifting through data and making subjective interpretations, you get a clear roadmap of where you need to put in the effort.

Sub sectional ability
estimates
Sub-sectional ability estimates - help
channelize energy

e-GMAT’s scoring engine then extracts sub-sectional ability scores so you know where you need to put in most effort.

For each focus area, you will get a time estimate.

This time estimate is based on data from 1000+students

Topic Level Analysis
– Sharpen The Lens
High Value Concepts

In sections where your ability is 70th percentile or higher, understand the topics where you faltered so that you can channelize your energy, fix your gaps, and get a higher score next time.

Those “close” but “incorrect” answers choices can be rejected using Visualization

Confused by lots of data – levege Simplification to get to the crux of the problem.

SIGma-X mocks Vs Official GMAT Mocks
High Value Concepts

SIGma-X GFE mocks go even further in terms of providing actionable insights to students. The table below showcases how the insights provided by SIGma-x mocks compare to those provided by the official mocks.

Those “close” but “incorrect” answers choices can be rejected using Visualization

Confused by lots of data – levege Simplification to get to the crux of the problem.

Insight on how it helps the students

Mocks

Official Mocks

Sectional Scores

It enables students to understand their current abilities in various sub-sections.

Sectional Gap

Students get a clear understanding of how much improvement they need in each section.

Sub-sectional abilities

Students understand where they faltered within a section. It helps them channelize their energy while crafting improvement plans.

Sub-sectional gap analysis

Students know how much they need to improve in a particular subsection to achieve their target sectional score.

Sub-sectional Accuracy Analysis

Students can estimate whether they lack conceptual understanding, standard application, or advanced application, further channelizing their energy.