Quantitative aptitude is a measure of an individual’s numeric ability and problem-solving skills. This sort of aptitude is highly valued in fields like computer science, engineering, and mathematics because it usually correlates with success in those fields.

However, there is a push to further this understanding in qualitative fields like journalism and the digital arts too. Companies and people are becoming more focused on understanding and improving quantitative aptitude through training and testing in the workplace.

Here’s what you need to know about quantitative aptitude and how to up yours.

**Here’s a Guide on How to Gauge Your Quantitative Aptitude**** **

**How is Quantitative Aptitude Tested?**

Gauging quantitative aptitude is a requirement on many important entry tests for different fields. It is also used in the job selection process for many companies including well-known ones like Goldman Sachs.

While quantitative aptitude is traditionally tested using, well, tests. There are other means of gauging that understanding, including through work-related projects like charting the spikes in google searches for a particular product or mapping demand for a service in a particular area.

**Types of Tests to Gauge Quantitative Aptitude**

There are a number of tests related to measuring quantitative aptitude, including common standardized tests like the SAT, ACT, and GRE.

However, other tests for measuring numeric ability and problem-solving skills are IQ tests, math tests, and application exams. Testing is the most common way of gauging the quantitative aptitude of an individual.

Major companies, especially tech companies, continue to use tests in their interview process to gauge this understanding.

**Topics Covered in Quantitative Aptitude Testing**

There are many topics covered in quantitative aptitude tests, which also vary by degree depending on how far along you are in understanding use-cases of quantitative aptitude. Some of the larger topic areas of quantitative aptitude testing include arithmetic, algebra, geometry, number systems, and modern mathematics.

Most of the topics are covered in middle school and high school. Developing a strong quantitative aptitude takes time, patience, and hard work to make good progress.

**A Further Breakdown of Topics**

Some books, like Quantitative Aptitude by R.S. Aggarwal, covering the topic of quantitative aptitude development suggests breaking down the larger topic into arithmetic ability and data interpretation.

The first subtopic, arithmetic ability, includes topics like averages, percentages, roots, and simplifications. The second subtopic, data interpretation, looks at an understanding of tabulation and various graphs like line graphs, bar graphs, and histograms.

**What Jobs Value Quantitative Aptitude**

While all fields should value a strong aptitude for problem solving and working with numbers, there are a number of fields that require an aptitude for those skills. Some of the most common fields where numeric ability and problem-solving skills are tested include engineering, actuarial science, computer science, economics, statistics, and mathematics.

Not all fields value quantitative aptitude in the same way, but there are commonalities. Those who work in quantitative fields are likely to have developed some of the following skills:

**Reasoning and Reverse Reasoning**

Logical reasoning is the ability to think through a problem step-by-step using analytics and deductive and inductive methodologies. The ability to think through a problem’s solution backwards is an important skill. It’s powerful in finding and understanding a methodology that works to solve the problem.

**Spatial and Abstract Relationships**

Knowing how to apply mathematical concepts and apply symbolism to express those concepts is important in communicating results in many heavily quantitative fields. It creates a standardized system to approaching problems among all practitioners within a particular field.

**Modeling**

The ability to choose from a number of mathematical models to communicate the best solutions to problems in various fields. Field experts, especially those in quantitative fields, need to model problems to communicate the best solutions to clients and to other stakeholders. Modeling also provides a methodology to approaching similar problems in the future.

**Attention to Detail**

Being accurate is important when working in quantitative fields, since job success depends on correct valuations and calculations. It is important to construct precise formulations and models to communicate solutions in mathematics and in writing.

**How to Further Develop your Quantitative Aptitude**

### Quantitative Aptitude Grows with Age

Research on productivity from the National Institute of Health shows that there are many ways in which changes in age can affect productivity, including on quantitative aptitude. Some of the studies also show a pattern where productivity peaks along with verbal and quantitative reasoning at around 40 years of age.

**Improving Quantitative Aptitude**

But, just like learning anything else, if you want to further your quantitative aptitude then you’ve got to practice using it.

The trick to improving is to understand that it is not about solving as many problems as possible correctly, but developing an understanding about how to approach many different problems using logic.

The logic and reasoning you develop from solving challenging problems leads to a better aptitude for numeric ability and problem-solving skills.

**Tips and Tricks to Solving Questions to Develop Quantitative Aptitude**

Some easy tricks to help you build a strong quantitative aptitude involve steps like underlining key bits of information in word problems and deriving formulas that are needed to solve the problem. It is better to grasp the logic given in the problem to find the next step instead of jumping to conclusions about given answers.

**Read Carefully**

Understanding all the components of a problem-solving question is an important starting point to building quantitative aptitude. Don’t underestimate the value of taking apart a question to understand what needs to be solved for.

**Pick at the Details**

Underline any details that would prove important pieces of information in solving through the problem. These will start to become relevant as you go through the step-by-step process of problem solving.

**Do Not Jump to Conclusions**

Grasp the logic of a question first without jumping to a conclusion about how to approach the problem. It is important to identify all the moving parts in a problem before putting pen to paper.

**Solve as Many Types of Questions as Possible**

Keep attempting many different kinds of problems because this will help build your familiarity in applying the prior three tips and tricks. It will also help you build your familiarity in approaching a wide variety of problem, including word problems, graphic problems, and much more.

**Keep Timing your Problem Solving**

As you start becoming familiar with a large cache of problem types, start timing your progress in attempting each type of problem.

Recording the time it takes you to solve particular problems will identify skills areas you need to improve on and those that you have already mastered. The point is to decrease your reaction time to many different problems by keeping up your practice.

**Improving Your Quantitative Aptitude Can Open New Doors**

While a quantitative aptitude can improve test taking capabilities and measure success for particular jobs, a strong quantitative aptitude also has the potential of strong personal enrichment.

**Computer Science and Data Science Projects**

Many fields like computer science and data science have general practitioners working on projects in their free time outside of their full-time jobs.

Strengthening quantitative aptitude can lead to exciting project ideas to pursue in those two fields and a better understanding of how to complete such kinds of projects. One platform to look for these kinds of ideas and projects is GitHub.

**The Future is Interconnected**

The discovery of new fields by combining a focus on strengthening quantitative analysis and numeric ability with other skill areas is a huge boon to the world. It allows us to become more collaborative and innovative in coming up with new ways to improve society and ourselves.

There is also a lot of potential to think up ideas to execute in other fields and work environments. One example is in journalism. Data journalism is a new and upcoming field within the last few years with a lot of potential to change the way we find and tell stories.

Without enthusiasts with strong quantitative aptitudes finding ways to contribute to their own specialized fields there would likely not be discoveries of certain collaborations like data journalism.