I was recently asked to give a talk to our graduate school annual conference. I offered several titles and the one they picked was Using R in research. I'm not sure if this was a good idea or not. The graduate school covers PhD students across three areas of the university: social sciences (including psychology), law and business. In addition the students tend to specialize in either qualitative or quantitive research methods, so I was talking to an audience who might know nothing about statistics or a great deal (e.g., several students have completed MSc courses in psychological research methods here or elsewhere).
My solution was try and explain the advantages of R relative to alternatives such as SPSS (probably the most common statistic package in the University). I also focussed a lot on graphical methods and simulation. It seemed to go quite well, but I worry that quite a few members of the audience were overwhelmed by large chunks of it.
I promised to put my slides on my blog - though I am not sure how useful they are to anybody who wasn't there. Without my commentary some (possibly most) of the slides won't make much sense. I spent a good deal of the time talking through exploratory plots of one data set (from Hayden, 2005). I use this example a lot in teaching and it involves a bit of class participating (guessing the origin of the data) - so I won't go into to detail here (lest I spoil it for future students), but you can google the original article if you are curious. I also spent some time on how R works (e.g., object types, assignment, basic modeling, plotting functions). My reasoning was that many of the audience have no familiarity with non-GUI interfaces in software and without explaining the basics of the interface they will not have the faintest clue how R works. For those with some familiarity (e.g., SPSS syntax) the examples were selected to show how powerful R can be for things like exploratory graphics.
Several students ask about resources for learning R. I mentioned some in earlier blog posts, but for psychologists Li and Baron's web resources are a good place to start. The other major resource is probably Quick R, but there are hundreds of other places to look online (depending on what stuff you need most).
Aug
17
I Will Not Ever, NEVER Run a MANOVA
I have been thinking to write a paper about MANOVA (and in particular why it should be avoided) for some time, but never got round to it. However, I recently discovered an excellent article by Francis Huang that pretty much sums up most of what I'd cover. In this blog post I'll just run through the main issues and refer you to Francis' paper for a more in-depth critique or the section on MANOVA in Serious Stats (Baguley, 2012).
Jan
19
A brief introduction to logistic regression
I wrote a brief introduction to logistic regression aimed at psychology students. You can take a look at the pdf here:
A more comprehensive introduction in terms of the generalised linear model can be found in my book:
Baguley, T. (2012). Serious stats: a guide to advanced statistics for the behavioral sciences. Palgrave Macmillan.
A more comprehensive introduction in terms of the generalised linear model can be found in my book:
Baguley, T. (2012). Serious stats: a guide to advanced statistics for the behavioral sciences. Palgrave Macmillan.
May
18
Serious Stats: Obtaining CIs for Spearman's rho or Kendall's tau
I wrote a short blog (with R Code) on how to calculate corrected CIs for rho and tau using the Fisher z transformation.
May
13
Serious stats: Type II versus Type III Sums of Squares
I have written a short article on Type II versus Type III SS in ANOVA-like models on my Serious Stats blog:
https://seriousstats.wordpress.com/2020/05/13/type-ii-and-type-iii-sums-of-squares-what-should-i-choose/
https://seriousstats.wordpress.com/2020/05/13/type-ii-and-type-iii-sums-of-squares-what-should-i-choose/
Sep
5
Egon Pearson correction for Chi-Square
I have just published a short blog on the Egon Pearson correction for the chi-square test. This includes links to an R function to run the corrected test (and also provides residual analyses for contingency tables).
The blog is here and the R function here.
The blog is here and the R function here.
Sep
15
Provisional programme: ESRC funded conference: Bayesian Data Analysis in the Social Sciences Curriculum (Nottingham, UK 29th Sept 2017)
Bayesian Data Analysis in the Social Sciences Curriculum
Supported by the ESRC’s Advanced Training Initiative
Venue: Bowden Room Nottingham Conference Centre
Burton Street, Nottingham, NG1 4BU
Booking information online
Provisional schedule:
Organizers:
Thom Baguley twitter: @seriousstats
Mark Andrews twitter: @xmjandrews
Supported by the ESRC’s Advanced Training Initiative
Venue: Bowden Room Nottingham Conference Centre
Burton Street, Nottingham, NG1 4BU
Booking information online
Provisional schedule:
Organizers:
Thom Baguley twitter: @seriousstats
Mark Andrews twitter: @xmjandrews
Jun
13
STOP PRESS Introductory Bayesian data analysis workshops for social scientists (June 2017 Nottingham UK)
The third and (possibly) final round of the workshops of our introductory workshops was overbooked in April, but we have managed to arrange some additional dates in June.
There are still places left on these. More details at: http://www.priorexposure.org.uk/
As with the last round we are planning a free R workshop before hand (reccomended if you need a refresher or have never used R before).
There are still places left on these. More details at: http://www.priorexposure.org.uk/
As with the last round we are planning a free R workshop before hand (reccomended if you need a refresher or have never used R before).
May
25
Serious Stats blog: CI for differences in independent R square coefficients
In my Serious Stats blog I have a new post on providing CIs for a difference between independent R square coefficients.
You can find the post there or go direct to the function hosted on RPubs. I have been experimenting with knitr but can't yet get the html from R Markdown to work with my blogger or wordpress blogs.
You can find the post there or go direct to the function hosted on RPubs. I have been experimenting with knitr but can't yet get the html from R Markdown to work with my blogger or wordpress blogs.
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