lawsofthought

library(tibble)

ilogit <- plogis # inverse logit 

Df <- tibble(corpus = c('bnc_subset', 'subset'),
             count = c(5242, 10092),
             total = c(27449, 56355))


M <- glm(cbind(count, total-count) ~ 0 + corpus, 

lawsofthought

library(plotrix)

# WHat follows is a copy and paste from
# https://www.rdocumentation.org/packages/plotrix/versions/3.7/topics/gantt.chart

Ymd.format<-"%Y/%m/%d"
gantt.info<-list(labels=
                   c("First task","Second task","Third task","Fourth task","Fifth task"),
                 starts=
                   as.POSIXct(strptime(

lawsofthought

library(dplyr)
library(ggplot2)
library(tidyr)
library(pwr)

sample_sizes <- seq(5, 100, by=5)
effect_sizes <- c(0.1, 0.3, 0.5)

sample_one <- function(sequence){
  sample(size=1, sequence)

lawsofthought

---
title: "Python code chunks in RMarkdown"
author: "Mark Andrews"
date: "29 December 2017"
output: pdf_document
---

Python and R code chunks in RMarkdown do not work the same. The R code chunks are all interpreted in one global environment, but the Python chunks are interpreted in independent environments. Also, I don't think there is any way to have Python inline code. 

The following chunks try to illustrate this.

lawsofthought

import cPickle as pickle

ongoing_list_dict = dict(subject_1 = 7,
                         subject_7 = 42,
                         subject_101 = 3)

# Write the dictionary to file
with open('ongoing_list.pkl', 'wb') as f:
    pickle.dump(ongoing_list_dict, f,  protocol=2)

lawsofthought

# Some R code to demo boxplots, beanplots, pirateplots, etc

library(psych)
library(dplyr)
library(tidyr)
library(beanplot)
library(yarrr)

# Load the cushny data
data(cushny)

lawsofthought

####################################
example.colors <- c('cyan',
                    'darkgoldenrod',
                    'cornflowerblue',
                    'chocolate1',
                    'chartreuse1')

myplot <- function(N, example.colors, drift=0.1, switch.p=0.01){
  
  K <- length(example.colors)