Wilson Morgado - 1º Congresso Online "A Estatística e suas possibilidades de atuação profissional"

Summary

The speaker reflects on the uncertainty of life and the role of probability in decision-making, especially in the field of statistics. They discuss the importance of understanding data, programming, and information processing, emphasizing the growing demand for data scientists. Their personal journey into statistics began unexpectedly, leading to significant professional experiences, including work in insurance, fraud detection, and statistical modeling. They highlight the evolving nature of statistics, particularly in computational intelligence, and stress its growing importance in diverse fields such as medicine, engineering, and social issues, encouraging a broader application of statistical knowledge for global problem-solving.

Takeaways

• 😀 Statistics is the study of probability and occurrences in life, providing insights into decision-making by modeling human intelligence through data.
• 😀 A strong foundation in programming and understanding information is crucial for those starting in statistics, as it goes beyond just mathematical concepts.
• 😀 Statisticians differ from other professionals like data scientists because they deeply understand statistical methods, which are essential for decision-making in various fields.
• 😀 The speaker initially pursued a career in production engineering but later switched to statistics after a professor's advice, leading to a fulfilling career in the field.
• 😀 Real-world applications of statistics are critical, as demonstrated by the speaker's experiences working in sectors like insurance, economics, and fraud detection.
• 😀 Working in insurance fraud prevention helped the speaker realize the importance of domain knowledge — understanding the data is as crucial as statistical expertise.
• 😀 The speaker's experience in academia, including pursuing a master's in engineering, emphasized the practical application of statistics rather than its theoretical aspects.
• 😀 Starting a company from scratch was a key goal for the speaker, who now operates a successful business in the insurance and financial sectors.
• 😀 In insurance, statistical models are used to predict risk, assess fraud, and price policies. Examples include using logistic models to assess accident risk based on demographic profiles.
• 😀 The future of statistics lies in improving speed and responsiveness in decision-making, and the field must evolve to incorporate faster data processing techniques like neural networks and AI.
• 😀 Statistics contributes significantly to various industries, such as medicine, engineering, marketing, and psychology, but there is an opportunity to apply it more broadly to address global social problems and improve quality of life.

Q & A

What is the relationship between statistics and decision-making according to the script?

Statistics plays a crucial role in decision-making by quantifying probabilities. It helps individuals assess the likelihood of various outcomes, enabling more informed decisions based on data, rather than intuition or emotion alone.

How does the script explain the importance of understanding programming and information when starting in statistics?

The script emphasizes that knowledge of programming and understanding information is more important than just learning statistics. A good statistician must be able to work with data, understand the context, and communicate insights effectively, which requires broader skills beyond just statistical knowledge.

What is the difference between statisticians and data scientists as highlighted in the script?

The script highlights that statisticians differ from data scientists primarily in their deep understanding of statistics. Statisticians focus on applying statistical principles to solve real-world problems, while data scientists also need expertise in programming, machine learning, and data engineering.

Why did the speaker initially choose to study statistics instead of engineering?

The speaker chose statistics over engineering after a conversation with a professor who suggested that statistics was a good fit for someone skilled in mathematics. The decision was influenced by the challenge that studying statistics presented at the time.

What role did the speaker's internship at an insurance company play in their career development?

The internship at the insurance company introduced the speaker to statistical modeling in the context of fraud detection and risk assessment. Although the internship was short-lived due to time constraints with studies, it provided valuable exposure to the practical application of statistics in business.

What was the speaker's first major professional experience in statistics?

The speaker's first major experience was working on fraud detection at an insurance company. This experience taught the speaker an important lesson: without proper understanding of the data and the domain, statistical models are ineffective.

How did the speaker further their expertise in statistics after their initial work experience?

The speaker pursued a master's degree in engineering, which provided practical experience and helped them understand the real-world application of statistics beyond theoretical knowledge.

What does the speaker identify as a significant challenge for statisticians today?

A significant challenge is the need for faster responses and real-time data processing. As the world changes rapidly, there is an increasing demand for statistics to evolve and provide quicker insights, requiring the use of computational intelligence and advanced tools like neural networks.

How has the use of statistics evolved in the insurance industry according to the script?

In the insurance industry, statistics is now used for more than just pricing; it is integral to detecting fraud, understanding customer profiles, and assessing risks. Statistical models help predict events, like car accidents, based on demographic and behavioral factors, which informs decision-making and pricing strategies.

What does the speaker believe is missing in the application of statistics today?

The speaker believes that statistics is often applied in a narrow, business-focused way, addressing specific company needs, but not enough attention is given to broader, global problems. They argue that statistics can contribute to solving social problems and improving lives on a larger scale, which is underutilized.