Amazing Facts About Computer Mathematics:

What Kind of Math Is Used in Computer Science?

Computer scientists use all different types of math. Those who work with advanced algorithms and matrices, like the kind involved in image recognition for medical diagnostics, need to understand higher-level concepts like differential equations.

Binary and Hexadecimal Counting

The binary number system uses only two digits, 0 and 1, to express all mathematical concepts. Computers use the binary system instead of the more common decimal system, so computer scientists need to know how it works.

Computers can read binary, but it can be inconvenient for humans to deal with. As an alternative, computer programming has turned to a system called hexadecimal, which uses all nine decimal digits and the letters A through F. It makes more sense to humans and converts electronically to binary.

Discrete Mathematics

Discrete math is tangible math. It analyzes the relationship between things that are distinct and separate. The concepts of discrete math include:

Probability
Combinatorics
Logic
Number theory
Graph theory

The problem-solving processes of discrete math are the basis of modern computer engineering. They power both simple and complex disciplines such as:

Computer architecture
Functional programming
Distributed systems
Machine learning and artificial intelligence

As a computer science professional, you might use discrete math to test out multiple algorithms and learn which is the most efficient. Meanwhile, the logical thinking you develop as a discrete math student will help you to approach programming and development tasks more methodically.

Statistics

Data has become an increasingly important aspect of scientific computing in the past few years, from machine learning to personalized app performance. This increased reliance on data has made statistics an important topic of study for all computer science students.

Statistics allow computer programs to deliver accurate generalizations and predictions based on available information. Understanding statistics can make it easier to grasp concepts like:

Data mining
Machine learning
Future modeling
Speech recognition
User responsiveness
Computer graphics analysis

The more you learn about statistics, the more adept you’ll become at managing and using complex data structures. This lets you write more advanced algorithms and push the envelope in software customization.

Linear Algebra

Computer science and software engineering rely on algorithms. An algorithm is a formula that takes you from a specific input to the correct output. If that sounds familiar, it may be reminding you of middle school or high school algebra.

Algebra includes concepts like:

Exponents
Polynomials
Linear equations
Quadratic equations

Each of these concepts has real world computer science applications. Understanding exponential relationships can help you to adapt visuals so they appeal to the eye. Solving linear equations helps with analysis of algorithms because it helps you to spot inaccuracies.

You can get by in software development without knowing much algebra, but learning it can help you to reach greater heights.

Calculus

If you plan to get a computer science degree, you’ll probably take a calculus course at some point.

There are two different types of calculus: integral calculus and differential calculus. Together, these disciplines help you to figure out rate of change, which is an important ingredient in many algorithms and programs.

Differential equations are particularly important. A differential equation calculates how something changes and how fast that happens, so a computer can predict future outputs. This helps with:

Designing simulations
Improving problem-solving programs
Creating effective algorithms
Developing accurate graphs