Welcome to my blog! I’ve been working at what I call “industrial statistics” and exploratory modeling for almost 30 years. I’ve dealt with a large range of data types and problem situations, and I find that my colleagues regard my judgment and insight.
I’ve learned that having a breadth of technical knowledge is critical, but when such knowledge is wedded to good judgment or intuition about meeting the needs of a particular situation or data set, great things can happen. In this blog, I hope to impart some of the intuition I’ve accumulated.
I’m writing this for data analysts and those who work with them. I don’t assume technical knowledge, but I do assume interest in strategies for meeting challenges and understanding features of data-based decision-making. This is not a “how-to”, but rather a “why-to”.
Please comment if you feel moved. I’m interested to hear your perspective on the topics I’m discussing.
You can be notified of new posts in one of the following ways:
- Subscribe to an e-mail notification.
- From a Fediverse account (such as a Mastodon account), you can follow {at jimg at replicate-stats.com}. (Put this address in the format @user@site-name. I have to write it this way because this editor automatically converts it to the address to my author profile.)
- Use an RSS reader and subscribe to https://www.replicate-stats.com/feed.
Essays
- June 2025 (1)
- April 2025 (2)
- March 2025 (4)
Comments
4 responses to “Welcome!”
Hey there, You have done a fantastic job. I will definitely digg it and personally recommend to my friends. I’m sure they will be benefited from this web site.
I’m so glad you found it useful! If there’s anything in particular you’d like me to discuss in the future on this blog, let me know. Perhaps send an e-mail to james at replicate-stats dot com (as if that will discourage any bots!).
This piece exudes a sense of calm certainty — the kind of writing that makes you feel grounded and at ease.
Thank you, I’m glad you have that feeling. I do want this blog to be welcoming and comprehensible to those who are interested in data analysis but don’t have a graduate degree in statistics, computer science, etc.