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Category Archives: .Interim directions
Picture break
Picture taken in San Francisco flower conservatory, a wonderful place with wonderfully informative guides. We will go on to a bit more model checking before considering the random effects formally.
Posted in .Interim directions
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Modelling – next steps
Having dwelt on the relationships between pairs of variables, both in terms of scatterplot depictions and, lately, in terms of correlations, we can move on to the real core of our focus in analyzing psycholinguistic data: linear regression. Creative commons … Continue reading
Modelling – moving on
Creative commons – flickr – Florida Memory: Young girl jumping on a trampoline at the Sarasota High School Sailor Circus We are now going to move into a new phase for these posts. We are heading toward a consideration of … Continue reading
Posted in .Interim directions, image, modelling, rstats
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Getting started – selecting data, wrangling data – early (basic) moves
This post and the few following will switch focus from the ML subject scores database to a database built out of normative data about word attributes, which actually comes in a number of different parts (downloadable at the links). Remember that … Continue reading
Posted in .Interim directions, getting started, rstats
Tagged csv, dataframe, normative
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Getting started – what’s next?
We will switch databases, to a set of data on item attributes. And we will work on another of the especially attractive and powerful features of R: the capacity to select and work with specific elements of a larger database: … Continue reading
Posted in .Interim directions, getting started, image
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Getting started – a quick word on destinations – plotting
A critical reason for learning to use R is the superior capacity that affords to visualize data. If you learn to plot data with R you are learning to plot data using the best tools now available. There are four … Continue reading
Posted in .Interim directions, plotting data, rstats
Tagged base, ggplot2, Graphics, grid, lattice, plot, visualization
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Plot your data
I would start plotting my data almost from the beginning. You can get an impression of how powerful the visualization capacity of R is from this gallery. There are multiple systems for doing graphics in R (cf. in SPSS where you … Continue reading
Posted in .Interim directions, plotting data, rstats
Tagged graph, plot, rstats, visualization
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What they call workflow
[Password protected version of this post, under resources, with downloadable example files] Many researchers talk about workflow. This refers to the series of steps involved in completing an investigation: going from intention to paper, to paraphrase the title of Levelt’s … Continue reading