Electrical engineering is one of the most math-heavy engineering disciplines, which probably explains its high dropout rates.
Applied statistics, in particular, feature heavily in many electrical engineering applications.
This article looks at the various ways in which the two disciplines differ from, and complement each other. It’ll help you decide which of them presents the best value to you.
Why Do Engineers Need Statistics?
Engineers have to come up with practical solutions to everyday problems in different fields and need to use statistical techniques to do things like probabilities, sampling and testing, and data analysis.
Depending on the field of specialization, statistics may also help engineers in areas such as:
- Estimating time and resources required in projects.
- Analysis of test and evaluation results on existing projects.
- Data collection and presentation.
- Interpretation of data prepared by others.
- Collaboration with other engineers and technicians.
Basically, it’s impossible to be a good engineer without some intermediate statistical knowledge and strong visualization and communication skills.
This is because most clients have little grasp of statistics and engineers need to simplify and present their data in ways that are appealing and understandable to clients.
Can An Engineer Become A Statistician?
Generally, statistics courses are less rigorous than engineering courses. As such, engineers looking to make the switch would find it very easy.
It’s also important to note that the degree requirements aren’t as strict in the statistics field as they are in engineering. So, engineers can master statistics in a matter of months.
Here are the four ways in which an engineer can transform into a statistician:
1. Get a Bachelor’s Degree in Statistics
If you’re an engineer in a field that’s not math-heavy, such as industrial or biomedical engineering, we strongly recommend getting a bachelor’s degree in statistics if you want to make a career switch.
This way, you’ll get all the basic statistical concepts you didn’t learn in your engineering undergraduate.
However, engineers in more mathematical fields, such as electrical, mechanical and petroleum don’t need to start at the bottom as they already have the basics covered.
2. Take the Necessary Short Courses
As mentioned above, some engineers only need to polish their statistical knowledge to become full-fledged statisticians.
Short courses in algebra, probability, and survey methodology – all of which are freely available online – will typically do the trick.
Mastering a few programming languages also helps if you wish to go deep into the data analysis field.
3. Get a Master’s Degree
Engineers looking for shorter transitions may choose to get post-graduate degrees in statistics as a way to beef up their statistical credentials.
Matter of fact, having an engineering degree qualifies one for direct entry to master’s programs in most universities.
Moreover, these programs only take 2-3 years and have flexible schedules so they won’t interfere with other activities.
4. Get an Entry-Level Statistics Job
Depending on the industry you work in, getting an entry-level statistics job may be the best way to gain the practical experience you need to become a statistician.
These jobs may include programming, data entry and presentation, and research assistant.
While it may be hard for a full-fledged engineer to “start from the bottom”, it’s absolutely essential to do so if you want to develop the needed skills.
It doesn’t have to be a full-time job or even a long-term. You can accomplish quite a lot in just a few months of commitment and discipline.
Is Statistics Useful For Electrical Engineering?
Statistics isn’t just useful but a key part of many electrical engineering jobs. This is because electrical systems and equipment are getting more complex with time and so are their datasets.
To effectively manage such quantities of data and subsequently get actionable insights from them, engineers utilize a variety of statistical tools like SAS, tables, and t-tests.
In particular, engineers working in power companies heavily rely on statistical models to estimate equipment lifespans, probability of failures and outages, and quality control.
Statistics is also heavily applied in manufacturing to determine component tolerance and equipment failure rates.
In the telecommunications field, electrical engineers apply statistics in signal processing, particularly to describe model parameters, pattern recognition, and non-linear filtering.
Is A Statistics Degree Harder Than Engineering?
Statistics isn’t harder than engineering. The engineering curriculum is more complex, stressful, and rigorous than statistics as it covers several fields like maths, physics, chemistry, programming, and statistics.
Statistics, on the other hand, mostly covers mathematical concepts and computer programming.
It’s also worth noting that engineering is harder to get into professionally as it’s highly regulated and you require a license, and a 5-year degree to practice in most countries.
Conversely, you can easily self-learn statistics and begin working within just a few months.
Should I Do Statistics Or Engineering?
If you’re good at maths, you’ll find statistics very easy and enjoyable. If you’re good at maths and physics and are interested in their applications, engineering may be the best option for you.
It all depends on your passions and strengths.
To give you a better idea of how each major fares, here’s a quick comparison:
| Statistics | Engineering | |
| Average Salary | $92,270 | $91,010 |
| Long Term Job Outlook | Good | Very Good |
| Job Flexibility | High | Moderate |
| Ease of Finding Employment | Moderate | Very High |
| Potential Jobs | Business Analyst Economist Financial Adviser Database Administrator Market Research | Data Engineer Industrial Engineer Mechanical Engineer Electrical Engineer Civil Engineer |
In Summary
As much as the two fields are fundamentally distinct from each other, there’s still a considerable amount of overlap between statistics and engineering.
The salary levels are almost the same – at least at the entry-level jobs – and as Big Data becomes more ubiquitous, both disciplines are only set to increase.
So, whichever major you choose, you can rest easy knowing you made a great decision.
