Sana Shafaqat Official

Will Statistics Ever Die?



Statistics is a valuable tool for understanding the world around us. The benefit of this analysis is that we can see patterns or trends in data sets, predict outcomes based on these patterns, and decide what steps to follow to address these trends. But what happens when statistics die? How do we go about collecting and analyzing data if we no longer have reliable methods for collecting and analyzing this type of data? What is the significance of this anyway, and why does it matter? As we explore these questions in this article, we’ll also examine how automating the statistical analysis of the data could make our lives more or less predictable based on our expectations.

What Is a Statistic?

Statistics studies the numbers associated with a random phenomenon to describe what happened. Using these numbers about the present and the past can be a helpful tool for making predictions and decisions. It is also possible to describe the present using statistics.

The word statistic comes from the Latin “stat,” which means “state” and “states.” The purpose of a statistical method is to collect data or conduct experiments on the subject in question, then to analyze those results using statistical methods such as probability theory and calculus (or sometimes calculus alone) before drawing any conclusions based on them.

Common Misconceptions

In statistics, it is essential to note that it is more than just counting numbers. A statistic is not simply a set of numbers; its definition includes much more than just a set of numbers. Although it is not a science, there are many scientific principles and techniques underlying statistical analysis. For example, you can use statistical analysis to predict the likelihood of an event occurring in the future based on past events happening at similar rates.

Statistics is also not math or data—it’s a way of looking at information that allows you to make better decisions based on the facts and figures presented. Many statisticians do not even refer to themselves as statisticians, as they feel this term implies a scientific approach that does not necessarily relate to everyday life; instead, they describe themselves as “quantitative analysts” or simply “statisticians.”

The History of Statistics

Statistics has a long and distinguished history as a field of study, a profession, and an art. We must first understand what statistics are before understanding how to use them. Statistics provide information about the world by describing its features in numbers.

Statistical predictions are based on these numbers because statisticians wish people to be able to make informed choices based on evidence rather than gut feelings or personal experience alone. If you want someone’s opinion on something but need proof of your own (e.g., ‘I believe this movie will be good), you can use statistics to persuade them otherwise.

The Death of Statistics?

Statistics is not dead, and it won’t be. There is no end to statistics, and there will never be one. Using statistics to gain a complete understanding of the world around us will always be possible. Using statistics allows us to determine our health and well-being and the well-being of individuals in our family and community.

There are also many applications for statistical data, such as making decisions about businesses, organizations, governments, and even countries. As the modern world has become increasingly complex, as a general rule, the use of statistics blurs the line between knowing something and making an informed decision. We must be mindful when we make decisions based on numbers alone (or worse, based on guesswork), for we might end up doing more harm than good to ourselves, others, or the environment.

Why Does This Matter?

Statistics is essential because it allows us to make better decisions. It’s the language of science, and scientists always rely on statistics. Businesses use it for everything from marketing strategies to predicting stock prices. There is a growing use of statistics by politicians when they want to understand how people will vote in the next election. And even criminal gangs use statistics to plan their operations based on how people will vote!

Statistics can help you understand what is happening and predict what will happen in the future. There were 80 cases of measles reported last year, but none so far this year (and there are none). So, if you are aware of that fact, then it may make sense to assume that fewer cases will be reported this year: fewer people got sick or more vaccinated children stayed healthy until they had their next vaccination (or both).

Don't Take Statistics for Face Value!

There are many ways to use statistics to gain a clearer picture of the world and prove a point. In this case, statistical manipulation refers to the manipulation of numbers to support an argument to benefit a particular viewpoint.

In other words, it’s okay to know that statistics are only sometimes accurate or fair, so you need to understand that. A good example would be if there were 5 million people in your neighborhood who lived below the poverty line (as defined by the Census Bureau), and it would appear that all of them were poor because all of them live in poverty! However, the truth is that only 3% of them live below the poverty line. However, in this particular case, and many other cases, it is essential to point out that the statistics have been manipulated in such a way that it appears there is something when there is none.

Automated Statistics and the Rise of Machine Learning

In recent years, automated statistics and machine learning have become more common. It is a great benefit to data scientists, who can now analyze data without going into a lab. However, when it comes to algorithms, it’s not only about how they can help you make better decisions-it’s also about what kinds of questions they can answer.

We will be able to accelerate our ability to learn from historical trends. As automation becomes more prevalent by using new methods such as deep learning, neural networks, natural language processing (NLP), chatbots, and augmented reality (AR), we can learn from historical trends more quickly.

Computational Thinking and the Death of Generalized Statistical Methods

The death of generalized statistical methods due to the rise of computational thinking is not inevitable nor an unavoidable consequence of their existence. It is a matter of choice: we can abandon or use them in a new way to achieve our goals.

In a nutshell, computational thinking is a way of thinking about problems, like how programmers and engineers think about issues in building things like cars and planes because they use it to solve them. There is a considerable difference between computational statistics and computational thinking, which is how you solve problems with computers – it’s an entirely different approach!

Statistical methods have always been intertwined with the history of computing power, from its inception as tabular data processing with punch cards through today’s world, where high-performance computers run simulations on billions (or even trillions) worth of data points every second. There has always been some element within these fields that drives innovation forward at an incredible pace!

The Future of Statistics?

Undoubtedly, statistics can be an invaluable tool in helping you make better decisions. Undoubtedly, statistics will always be vital in our lives since they can help us understand the world around us. For example, in medicine, statistics are used to study diseases and find ways to prevent them from spreading among people who are sick or injured.

The future of statistics depends on you! You can help make the world safer by continuing to use this valuable resource and sharing your knowledge with others who may need assistance in using their own data collection methods (or just having fun doing something new).


The power of statistics is undeniable, but you need other tools to succeed. To be a practical statistician, you must think statistically, but more is required. While statistical methods are helpful in many situations, they shouldn’t be the only methods you use. When making decisions, you should use both quantitative and qualitative factors.


You may have heard some people say that statistics is dead, but that is not the case. Throughout our lifetimes, statistics will continually evolve as the world around us evolves. It has been significant to see how statistics have evolved from a relatively straightforward method of collecting and analyzing data using simple statistical analysis.

While this may seem bad at first glance, why would anyone want more than one tool? As a result, researchers have even more opportunities to gain a deeper understanding of their audiences through tracking techniques such as mouse movements on web pages or clicks on advertisements. Businesses can use these insights to improve their business strategies by understanding which marketing campaigns work well together according to their target audience.


There has been a great deal of exaggeration regarding the death of statistics. Using statistics is a fundamental part of many disciplines and will remain so for many years. Statistics can teach us a lot that algorithms or computer models cannot, even if they do improve in analyzing things such as Twitter users and chess players with time.

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Sana Shafaqat

Sana Shafaqat

I am a professional statistician and data analyst. I have worked in the field for over five years and have experience with various statistical software packages. I am passionate about data analysis and interpretation and love finding new ways to visualize data. I enjoy reading, spending time with my family, and playing tennis in my spare time.

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