Browse by category
Tags
- 2012
- anova()
- arrays
- bluff
- california
- cbind()
- collinearity
- correlation
- correlations
- csv
- dataframe
- dataframes
- distribution
- DMDX
- evernote
- Exploratory data analysis
- facet
- Flickr
- getting started
- ggplot
- ggplot2
- graph
- Graphics
- grid
- GUI
- help
- histogram
- ifelse
- july
- label
- lattice
- learnR
- learn R
- library
- LME
- lmer()
- matrices
- matrix
- merge
- mixed effects
- modes
- multicollinearity
- normative
- objects
- ols()
- package
- plot
- plyr
- productivity
- programming
- R-Studio
- rbind()
- regression
- rename
- rstats
- santacruz
- scatterplot
- Scatter plot
- smoother
- social
- statistical concepts
- subset
- summary
- t-test
- title
- utah
- variable
- vector
- vectors
- visualization
- why R?
- workflow
- working directory
- workspace
-
Join 26 other subscribers
-
Recent Posts
- Getting started — loading data, writing and saving scripts January 16, 2014
- Getting started – getting helped January 16, 2014
- Getting started — Installation of RStudio and some packages + using ggplot() to make a simple plot January 16, 2014
- Postgraduate data analysis and interpretation January 16, 2014
- Mixed-effects modeling — four hour workshop — part IV: LMEs November 5, 2013
Category Archives: modelling
Modelling – some conceptual foundations
We have discussed the relationships between pairs of variables, we will now move on to analyzing our data using linear regression. Slides on regression can be downloaded here. You will see in those slides that I rely very heavily on … Continue reading
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 – examination correlations: advanced scatterplots
This post will focus exclusively on the relationships between pairs of variables. We will be looking at the item norms data, though you might want to practice the R procedures we deploy on the subjects data (see earlier posts here, … Continue reading
Posted in 12. Modelling - scatterplots+, modelling, rstats
Tagged correlation, scatterplot
Leave a comment
Modelling – examining correlations: first, look at predictor distributions
This post follows on from the previous post, concerning the examination of variable distributions. It is always useful to plot the distribution of variables like item attributes e.g. item length in letters. One important benefit of doing so is identifying … Continue reading
Posted in 11. Modelling - distributions, modelling, rstats
Tagged describeBy, statistics, summary, t-test
Leave a comment
Modelling – examining correlations: first, look at predictor distributions
This post will take a more in-depth look at the relationships between variables. A key property of experimental data is that we measure attributes – characteristics of people, stimuli, and behaviour – and that those measurements (the numbers) vary. Numbers … Continue reading
Posted in 11. Modelling - distributions, modelling, plotting data, rstats
Tagged density, distribution, grid, histogram, pdf, t-test
Leave a comment
Modelling – examining the correlations between predictor variables
This post will consider how to explore the relationship between a set of variables: variables that we will ultimately use in a mixed-effects analysis of lexical decision data. Most of the analyses we will be doing will examine whether observed … Continue reading
Posted in 10. Modelling - collinearity, modelling, rstats
Tagged collinearity, correlation, multicollinearity, regression
Leave a comment
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
Leave a comment
Getting started – statistical concepts – correlations
As we advance through the capabilities of R, we will increasingly take on the development of understanding of key statistical concepts. I have uploaded some undergraduate-level slides on correlations here: https://speakerdeck.com/robayedavies/r-class-correlations — check them out or, better, read a chapter … Continue reading