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Nina Anderson
Data Scientist

Nina is a data scientist at AMT – Association for Manufacturing ¶¼ÁéÌåÓýÖ±²¥, where she is an active practitioner and speaks about data science principles. Her work at AMT supports holistically understanding data and collaborating on its business value. Topics she enjoys discussing include statistical engineering, mathematical statistics, and coffee.

Nina is a data scientist at AMT – Association for Manufacturing ¶¼ÁéÌåÓýÖ±²¥, where she is an active practitioner and speaks about data science principles. Her work at AMT supports holistically understanding data and collaborating on its business value. Topics she enjoys discussing include statistical engineering, mathematical statistics, and coffee.

Posts by Nina Anderson
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By Nina AndersonJul 18, 2024

Trends in Utilizing AI To Complement Integrated Force Control

AI and advanced sensors transform robotics, enabling direct force control with feedback. This article explores AI's role in integrated force control, predictive modeling, and their impact on robotic performance and end effectors across applications.

5m read
Intelligence
By Nina AndersonMay 23, 2023

Derivative, Meet Gradient

Does a year-over-year percentage growth truly reflect industry change? Do increased robot installations in sectors with less robot density look the same in ones with more density? Derivatives help expose how total change is affected when variables change.

5m read
Intelligence
By Nina AndersonNov 18, 2021

If Something Is True, Does It Mean It's Important? Understanding Statistical Significance

The statistical perspective of significance should not be confused with the practical sense of significance. Consider the difference between something having strategic importance versus something being statistically significant.

5m read
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By Nina AndersonOct 01, 2021

How Do You Make Sense of Data That You’ve Never Seen?

How do you make sense of data that you’ve never seen? This article provides a first-line approach on garnering data insights after the data has been initially retrieved.

7m read