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Why Is Statistics Important?
06.08.2023 • 4 min read
Sarah Thomas
Subject Matter Expert
This article explains why statistics is important and why it’s essential in society. We’ll give you the top reasons with examples.
In This Article
At 8:33 am on April 20th, 2023, Space X launched its Starship and Super Heavy rocket from its Starbase spaceport in Boca Chica, Texas. The Starship climbed 39km over the Gulf of Mexico before multiple engines started to fail.
Four minutes after takeoff, it exploded into a million pieces showering smoke and debris over the launch pad. Despite the explosion, the SpaceX team and the crowd watching cheered. The launch brought SpaceX one step closer to producing a revolutionary new spacecraft that might someday transport crew and cargo around Earth’s orbit or even to the moon or Mars!
When you look at a rocket, you may think about the physics and engineering that go into building it. But rocket launches and space navigation are as much a feat of statistics as they are of physics and engineering.
Not only do engineers and data scientists at SpaceX rely on statistics to evaluate the safety and performance of their missions. SpaceX—as a business—depends on statistics to model the company’s finances and future success.
It may not always be obvious to you, but if you look closely, statistics are everywhere. In this article, we’ll explain the relevance of statistics and why you should consider studying it.
Importance of Statistics
Statistics is the science of collecting, summarizing, and learning from data. As an applied field, we use statistics in many different disciplines, jobs, and aspects of our day-to-day lives.
Here are some examples:
Climate scientists use statistics to build climate models.
AI chatbots, like ChatGPT, use statistics to string together words and intelligently respond to our queries.
Politicians use statistics to understand their voters and improve their chances of winning elections.
In the world of sports, coaches, managers, and recruiters use statistics to find untapped talent and improve the performance of their teams.
When you check your fitness tracker or try to improve your following on social media, you are relying on stats.
You may think statistics is some esoteric discipline only studied by statisticians with PhDs, but that’s not the case. Statistics is a skill you can use to solve problems and deepen your understanding in various areas!
10 Reasons Statistics Is Important
Here are 10 reasons statistics is important, useful, and well worth studying.
1. Helps you make decisions based on evidence and data
Statistics provides insights into different situations and helps us make informed decisions. It allows you to test whether your strongly held opinions and beliefs are backed by empirical evidence.
2. Helps you make convincing arguments
Two main parts of statistics exist: inferential statistics and descriptive statistics. In statistical inference, you’ll learn how to analyze data and look for evidence to support any number of hypotheses. Once you’ve learned something from your data, you can use descriptive statistics to summarize and present your findings using charts, graphs, tables, and other more advanced data visualizations.
3. Helps you make predictions
A major application of statistics is prediction. You can use statistics to analyze past data and make predictions about future outcomes and events. Computer scientists, sports betters, businesses, and investors all use statistics for prediction and forecasting.
4. Is a powerful research tool
Statistics is an important tool in academic research. By collecting and analyzing data, researchers deepen their understanding of the subject they study. This helps spawn new ideas, theories, and concepts.
5. Gives you hidden insights
Statistics can show you things you might not have seen otherwise. One of the most exciting aspects of statistics is running into counterintuitive findings that confront your assumptions about the world.
6. Has applications in medicine and public health
Cures for cancer, new treatments for Alzheimer's, and vaccines for highly transmissible diseases—are all being developed using statistical analysis. Pharmaceutical companies, doctors, and medical researchers use statistical experiments like randomized control trials to develop new treatments and to detect and mitigate serious side effects.
7. Has applications in business, economics, and politics
Statistics is central to business, economics, and politics. Companies use statistics to learn about their customers, make predictions about market trends, and improve their products. Economists use statistics to study finance, inequality, and business cycles. Politicians and their staff use statistics to navigate elections, poll voters on important issues, and to develop policies.
8. Helps researchers fight climate change
Without statistics, climate scientists couldn’t predict future weather patterns, global temperatures, or emissions. Companies and governments couldn’t analyze the impact of climate-friendly products and policies.
9. Plays a major role in new technology development
Artificial intelligence is one of the most important new technologies of our time. Computer and data scientists working on problems like machine learning, deep learning, and neural networks use statistics to build programs and machines that mimic human intelligence.
10. Use it in everyday life
Statistics helps you navigate your daily life. You can use statistics to improve your health and fitness and your finances and productivity. You can even find applications for it in hobbies like gardening, developing a side hustle, playing poker, or analyzing sports.
Consider Taking an Introductory Statistics Course
Even if you don’t plan on becoming a full-time statistician, within the field of statistics, there is a lot to gain by just taking a course or two in high school or college.
Here’s a list of statistical skills you can build in an introductory statistics course:
Working with different data types and data collection methods. You’ll learn to differentiate between big data, observational data, and experimental data, and you’ll learn to differentiate between good and bad sampling techniques.
The basics of descriptive statistics. You’ll learn how to calculate summary statistics and how to present data in graphs, tables, and charts.
You’ll learn how to work with powerful theories in probability, like the central limit theorem.
Statistical inference. Working with sample data sets, you’ll be able to uncover powerful insights you might otherwise have missed.
Hypothesis testing. In hypothesis testing, you’ll learn how to assess how reliable your statistical results are.
Correlation and causality. Using linear regression models, you’ll learn to model and measure the relationship between two or more variables.
A little bit of statistical knowledge goes a long way, and what you learn can be carried over into plenty of other fields like computer science, the social sciences, and medicine.
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