# Discrete Maths or Statistics

• Solidmozza
In summary, the conversation is discussing which first year university subject would be more beneficial for someone interested in majoring in chemistry or physics. The two options are Discrete Mathematics, which focuses on Catalan Numbers and fundamental aspects of discrete math, and Statistics, which covers data analysis, probability, and inference. The consensus seems to be that Statistics would be more useful for both potential majors, although Discrete Mathematics may have some relevance to chemistry. Ultimately, the choice depends on personal preference and interest in mathematics.
Solidmozza
Hi all,
I was just wondering which would be the more beneficial first year uni subject to take given that I would like to major in either chemistry or physics - Discrete Mathematics or Statistics.
The Discrete maths course "focuses on the enumeration of the Catalan Numbers" and is an introduction to fundamental aspects of discrete mathematics. The Statistics course includes work on Data Analysis, Probability and Inference.
At the moment, I am thinking that Statistics would probably be the more beneficial course to take, but the Discrete Maths one seems more interesting.

Any opinions would be greatly appreciated!
Thanks!

Statistics would be more useful in general for both potential majors.

I agrree with maxwell, discrete math is very abstract concepts that would help a computer science major but a chemistry or physics major i don't see it being more useful than stats.

If you don't have to take Discrete Math for your Chemistry degree, then I would opt for Statistics. The only reason I can say this is because Discrete Math is for people with an IT link to programming. =o)
Algorithms, Trominoes and Pigeon Hole Principles which (this one) might pertain to Chemistry. =o) Just my personal opinion! We can only offer you suggestions, but you must choose!

If you enjoy maths, take both. Extra maths don't hurt. However, if you only want to take one, I would go for Stats like everyone else says.

## 1. What is the difference between discrete math and statistics?

Discrete math is a branch of mathematics that deals with discrete objects and structures, such as integers, graphs, and trees. It is used to model and analyze systems that have a finite or countable number of possible outcomes. Statistics, on the other hand, is a branch of mathematics that deals with the collection, analysis, interpretation, presentation, and organization of data. It is used to make inferences and predictions about a population based on a sample of data.

## 2. How are discrete math and statistics used in real life?

Discrete math is used in various fields such as computer science, engineering, and physics, to solve problems related to algorithms, networks, and optimization. Statistics is used in fields such as economics, psychology, and biology to analyze data, make predictions, and test hypotheses. It is also used in everyday situations, such as polling data for elections and analyzing trends in stock markets.

## 3. What are some common applications of discrete math?

Discrete math has a wide range of applications, including cryptography, computer science, game theory, and operations research. It is used to design efficient algorithms, develop secure communication systems, and model decision-making processes. It is also used in combinatorics to solve problems related to counting and probability.

## 4. How does statistics help in decision making?

Statistics provides tools and techniques for analyzing data and making informed decisions based on the results. It helps to identify patterns and trends in data, make predictions and forecasts, and test hypotheses. In business, statistics is used to analyze market trends, customer behavior, and make strategic decisions. In medicine, it is used to evaluate the effectiveness of treatments and identify risk factors for diseases.

## 5. What are some common misconceptions about discrete math and statistics?

One common misconception is that discrete math is only used in computer science or engineering, when in fact it has applications in many other fields. Another misconception is that statistics is all about numbers and calculations, when in reality it also involves critical thinking, problem-solving, and interpretation of results. Lastly, many people believe that statistics can prove causation, but it can only show correlation and does not necessarily imply causation.

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