ITNS–The Second Edition!

Routledge, our publisher, has started planning for a second edition. That’s very exciting news! The only problem is that Bob and I can’t think of anything that needs improving. Ha! But, seriously, we’d love to hear from you about things we should revise, update, or somehow improve. (Of course, we’d also love to hear about the good aspects.) We’d especially like to hear from:

Teachers who are using ITNS. What do you like? What’s missing? What are the irritations? What difficulties have you encountered?

Students who are using ITNS. Same questions! Also, how could the book be more appealing, accessible, effective, even fun?

Potential teachers. You have considered ITNS, perhaps examining an inspection copy, but you decided against adoption. Why? Was it mainly the book and ancillaries, or outside factors? How could we revise so that you would elect to adopt?

The Routledge marketing gurus tell us that one strong message back from the field is: “ITNS is really good, just what the world needs and should be using. But for me, right now, it’s too hard to change. I’ll wait until others are using it, maybe until I’m forced to change.” If that’s how you feel, please let us know.

Perhaps that position is understandable, but it seems to conflict with the enthusiasm with which some (many?) young researchers are embracing Open Science, and the major changes to research practices that Open Science requires. Consider, for example, the emergence of SIPS and, just recently, the Down-Under version.

That position (i.e., it’s too hard to change right now) also contrasts strongly with the strong and positive responses that Bob and I get whenever we give talks or workshops about the new statistics and Open Science.

So we’re puzzled why more teachers are not yet switching their teaching approach–we’ve tried hard to make ITNS and, especially, its ancillaries as helpful as we can for anyone wishing to make the switch.

Thinking about how we could improve ITNS, here are a few of the issues you may care to comment about:

Open Science Lots has happened since we finalised the text of ITNS. We would certainly revise the examples and update our report of how Open Science is progressing. However, the basics of Open Science, as discussed in Chapter 1 and several later chapters, endure. ITNS is the first introductory text to integrate Open Science ideas all through, so we had to figure out for ourselves how best to do that. How could we do it better?

ESCI ESCI is intended to make basic statistical ideas vivid, memorable, and easy to grasp. It also allows you to analyse your own data and picture the results, for a range of measures and simple designs. Many of the figures in the book are ESCI images. However, in ESCI you can’t, for example, easily load, save, and manage files. The online ancillaries include workbooks with guidance for using ITNS with SPSS, and with R. Should we consider replacing ESCI, noting that we want to retain the graphics and simulations to support learning? Should we retain ESCI, but include more support for Jamovi, JASP, or something else? Other strategies we should consider?

NHST and p values We present these in Chapter 6, after the basics of descriptives, sampling, and estimation in earlier chapters. You can elect to skip this chapter, or give it as little or as much emphasis as you wish. Is this the best chapter organisation?

Ancillaries We offer a wide range via the publisher’s companion website. What’s most useful? Least useful? How could we improve the ancillaries?

…they are just a few thoughts. Tell us about anything you wish. You could even tell us it’s all wonderful, if you like!

In advance, many thanks,

P.S. Make a public comment below, and/or email either of us, off list:

4 comments on “ITNS–The Second Edition!
  1. I love ESCI, but loading up Excel is a hurdle to showing it to other people. HTML and Javascript probably offer the least resistance to sharing.

    For example, I made this Javascript version of the “Dance of the CIs”:

    • Geoff Cumming says:

      Hi Paul,
      Thanks, that’s great. We appreciate the issues with Excel, including the lack of perfect compatability with Mac. Bob has some prototypes of various different approaches to building the simulations. The software decisions are critical, not least because any major change would be a very large task.
      BTW, it’s good to see prediction intervals, and essential to have the definition at the bottom. My first inclination is to assume ‘prediction interval’ refers to an interval with a stated probability of including the mean of a replication, rather than a single data value. But, as you know, the term does not have a single agreed usage.

  2. Ah, sorry. I’ve now added prediction intervals for the mean of replication.

    The only other thing I can say from my own experience is that the R shiny library is easy to get things running in, but can feel clunky to use, and hosting applications is potentially a problem. One potentially interesting use of shiny would be to offer a package in which some of the functions open small shiny apps to interact with.

Leave a Reply

Your email address will not be published. Required fields are marked *