For those with a similar lack of focus I would suggest perusing the listings of the GIS and Science blog. It is basically just listings of various research endeavors that have some relationship to geographical analysis, and so should qualify as "I am interested in learning from a layperson point of view what some of this language means and how to apply it to everyday GIS."
I most frequently encounter the adjective of geostatistics in conjunction with data analysis in the natural/environmental sciences. Examples of this are the texts Cressie (1993) or Isaaks and Srivastava (1989).
It is used far less frequently with statistical techniques more common in the social sciences. Examples of frequently cited texts focused on statistical analysis in the social sciences (but with an obvious focus on geography) are Anselin (1988), Waller and Gotway (2004), Lesage and Pace (2009), Ward and Gleditsch (2007). Books that might be considered a good bridge between the two fields might be Haining (2003) and Ripley (2004) (as well as the Bivand book cited by dslamb).
I list these because I don't necessarily endorse the distinction between the two fields (how can Moran's I not be considered a geostatistic?) But that being said, most people won't be particularly interested in all of those topical domains. Partly the reason that the distinction exists has to do with the type of data the statistical techniques are applied to, and hence if you are specifically interested in analyzing topical materials that are on one side the other may not be all that applicable. This is also the reason I suggested the GIS and Science blog, as they have listings falling under both of those categories. Although my interests largely remain in the social science realm, I still see articles more oriented towards the natural sciences that I find interesting (such as Visual Comparison of Moving Window Kriging models, now thats just cool!)
Now that I have inundated you with a plethora of expensive textbooks, are you still interested in all of geostatistics, or would your interests perhaps be slightly smaller in scope?
I frequently find that looking within software manuals are good places for definitions (and sometimes broader examples of applications). For example I came across the PASSaGE software when I was looking up a formula for local Geary's c. The GeoDa workbook is a wonderful introduction to spatial regression, and I've been told the manual/tutorials for the ClusterSeer software is a good introduction to cluster analysis (although unfortunately they do not have it available online it appears). For point pattern analysis CrimeStat is a very good reference.
Since I can imagine that learning the material in course format as opposed to a book is easier for some, I might suggest checking out if one of Pierre Goovaerts short courses on environmental geostatistics are coming nearby, and I see ICPSR has two courses related to spatial econometrics listed on their site (1,2, as a note these links will likely become outdated in the fairly near future). For entirely online material (and those of us who are more frugal), you can peruse the listings of MIT's open courses or for applied analysis using the R software you can work your way through the spatstat tutorial.
Also since travelling 1000 miles for a course is rarely feasible, if you find a course that looks interesting asking the professor for a copy of a syllabus is a good way to identify pertinent reading material. There was recently a post on the stats site asking for software recommendations to estimate variograms, and I would think it is likely there are some more useful sources of learning material listed on that thread.
Just to continue on rambling with resources I have collated, besides the Hengl (2009) book that was already listed in your question, below are other websites with various resources;
- CATMOG (A note, these are a good place to start for an introduction to the specific topical material that is covered)
- Geospatial Analysis - A comprehensive guide (de Smith, Longley, and Goodchild, 2006) which I am sure has been cited here multiple times.
- The Center for Spatially Integrated Social Science has a host of resources.
- For resources related to visualization I have found GeoVista, and the Spatial Data Mining and Visual Analytics lab to have some pretty cool stuff.
- The resources at the Geoda center are worth mentioning a second time (although they could perhaps use some better organization!) @Laurent mentions the tutorials page, which has some software tutorials for spatial regression, point pattern analysis, and variography in different software packages. I was recently forwarded a page of e-presentations from them as well. It is probably the most wide variety of spatial analysis presentations I have ever seen, spanning the divide between natural and social science techniques I discussed earlier in the post. I haven't gone through the slides, but I highly suspect they are a good introduction to any of the topics they cover (and likely less intimidating an introduction than from some of the text-books I listed prior). I find new things on that site every time I peruse it, it is worth mucking around to see if I missed anything.