steveharoz

steveharoz

library(tidyverse)
library(foreign) # for read.spss()
library(ggdist) # for geom_dots()


# load the data
# source: https://osf.io/sd76g/
data = foreign::read.spss("data_Experiment_4.sav", to.data.frame=TRUE) %>% 
  as_tibble()

steveharoz

library(tidyverse)
library(lmerTest)

# subject count
COUNT = 5

set.seed(8675309)

# generate a unique intercept per subject
data = tibble(

steveharoz

steveharoz

# Extract all citation numbers such as [1] from a PDF's text
# It also includes cases for multiples [1, 3] and ranges [1-5]
# It tries to exclude confidence intervals by skipping 
#
# written by Steve Haroz with help from ChatGPT
# MIT license

library(tidyverse)
library(pdftools)

steveharoz

COUNT = 100000

# How often does a single t-test of random data yield p<0.05?
replicate(COUNT, 
  t.test(rnorm(20))$p.value < 0.05
) %>% mean()

#> 0.05073
# 5% false positive rate

steveharoz

directed-graph-creator

Interactive tool for creating directed graphs, created using d3.js.

Operation:

• drag/scroll to translate/zoom the graph
• shift-click on graph to create a node
• shift-click on a node and then drag to another node to connect them with a directed edge

steveharoz

library(tidyverse)

COUNT = 40

data = tibble(
  car = paste0(sample(LETTERS, COUNT, TRUE), sample(letters, COUNT, TRUE), sample(letters, COUNT, TRUE)),
  value = rnorm(COUNT, 3),
  group = c(rep("Petrol", COUNT/2), rep("Hybrid", COUNT/4), rep("Pure Electric", COUNT/8), rep("Diesel", COUNT/8))
)

steveharoz

StatEndpoint <- ggproto("StatEndpoint", Stat,
  compute_group = function(data, scales) {
    # sort by x so indexing is meaningful
    data = arrange(data, x)
    # grab only the first and last row
    data[c(1,nrow(data)),]
  },
  
  required_aes = c("x", "y")
)

steveharoz

height: 600