Statistical modeling: understand what it is and why it's worth including this knowledge in your professional training.
According to a study by BI-Survey, approximately 60% of high-performing companies base their decisions on data.. Regardless of the sector, businesses are increasingly seeking professionals who know how to use data collection and analysis techniques, such as statistical modeling.
In this text, we will explain what this tool is, how it is used in practice in companies, and why acquiring this skill can boost your career.
What is statistical modeling?
Statistical modeling is a technique that uses mathematical and statistical tools to create simplified representations of reality. Basically, Modeling transforms a set of information into formulas or equations that describe how different variables are related..
These results are based on data and serve to understand patterns, predict scenarios, and help in making more informed decisions.
There are several areas in which statistical modeling can be applied, such as economy, biology, marketing, and engineering. Economists, for example, can use this strategy to predict a country's economic growth, while companies can use it to understand consumer behavior and create more effective marketing strategies.
One of the main differences between statistical modeling and other forms of data analysis, such as descriptive analysis, is that modeling goes beyond simply observing the data; instead of just writing down what happened, seeks to understand underlying relationships between variables and to make predictions about the future.
Thus, it also differs from machine learning approaches, For example, because it focuses more on the automation and adaptability of algorithms.
Read more: Discover now how to stand out in the Engineering market!
How is statistical data modeling used in practice?
Okay, so far you've understood what data modeling is and how it differs from other analysis strategies. But how does it work in practice?
This strategy follows a few basic steps that transform raw data into useful concepts. Check it out:
- Data collection — gathering relevant information about the problem to be analyzed;
- Cleaning and organizing the data — removal of outliers, also known as inconsistencies, that may distort the results;
- Choosing the modeling structure — selecting an appropriate method, such as linear regression, based on the purpose of the analysis;
- Training and testing of the model — using a sample of the data for training and testing, ensuring its accuracy;
- Results forecast — After the test, use a larger sample size to make predictions based on the model.
To optimize processes and improve decision-making, many companies use statistical modeling. One of them is Amazon, which uses statistical models to predict product demand, thus optimizing inventory and improving delivery times.
Read more: What is Data Science and what are its trends in the job market?
Why can learning statistical modeling boost your career?
Learning statistical modeling can significantly boost your career, especially because We are in a job market that is increasingly data-driven..
Companies across a wide range of sectors are seeking professionals capable of analyzing large volumes of information and making evidence-based strategic decisions.
Furthermore, the market is highly competitive, so mastering statistical modeling will be a significant advantage in becoming a more attractive candidate for positions involving data analysis.
Sectors such as Business, healthcare, economics, technology, and engineering are major users of statistical modeling. And mastering this tool is almost indispensable for anyone who wants to succeed in these areas.
Furthermore, for those working in data science, statistical modeling is an essential skill in the age of... Big DataWith the explosion of data generated daily, organizations need specialists who can identify patterns, predict behaviors, and optimize processes based on concrete information.
Read more: Data engineer: a trending profession for the future.
Statistical modeling courses: how to choose the best training
If you are interested in the field of statistical modeling, it is important to consider some key points when choosing your course to ensure relevant training aligned with market needs.
First, check if the course covers both theoretical fundamentals and practical application. Quality classes should teach the use of statistical tools such as R, Python, and analysis software like SPSS or... Excel, In addition to offering real-world case studies.
Another important point is flexibility: whether you prefer online or in-person classes, look for options that fit into your routine and provide interactive learning.
A ESEG College This is an excellent opportunity for those who wish to specialize in statistical modeling: the institution combines theory with practice and uses innovative methodologies to help students prepare for the challenges of the job market.
Featuring a team of highly qualified teachers and a modern structure, ESEG is currently one of the leading universities in the city of São Paulo, and this extends to its Professional Development courses, such as Statistical Modeling..
Therefore, by learning about the field of statistical modeling, the job opportunities available in the market, and how ESEG will help you obtain the necessary qualifications, you are one step closer to entering this very promising area. Access the page for our Statistical Modeling course. and secure your spot!
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