Many, even most, studies that contain a statistical component use frequentist, also called classical, techniques. The gist of those methods is this: data is collected, a probability model for that data is […]
AMS conference report: day 4
The AMS is re-issuing its statement on the necessity of using probability in forecasts. I am on the committee that is re-drafting, or, as they to say, “wordsmithing”, it. If you know […]
Has atmospheric CO2 decreased? A different way to look at CO2 changes
Joe Daleo, the number one guy over at Icecap.us, recently sent me the CDIAC (ice core) CO2 data as criticized in Beck (2007) and asked me what I made of it. Now, […]
Do not calculate correlations after smoothing data
This subject comes up so often and in so many places, and so many people ask me about it, that I thought a short explanation would be appropriate. You may also search […]
Stats 101: Chapter 6
It was one of those days yesterday. I got two chapters up, but did not give anybody a way to get them! Here it is These are the last two “basics” Chapters. […]
Why most statistics don’t mean what you think they do: Part II.
In Part I of this post, we started with a typical problem: which of two advertising campaigns was “better” in terms of generating more sales. Campaigns A and B were each tested […]
Why most statistics don’t mean what you think they do: Part I.
Here’s a common, classical statistics problem. Uncle Ted’s chain of Kill ’em and Grill ’em Venison Burgers tested two ad campaigns, A and B, and measured the sales of sausage sandwiches for […]
Heartland conference: day 3 and wrap up
Czech Republic President Vaclav Klaus started off the day with a rousing speech. I hadn’t known he was an economist, but it was obvious quickly through his use of phrases like “maximize […]
Recent Comments