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Math 268 Pathways, data organisation, making univariate plots (ggplot2),…
Math 268 Pathways
data organisation
relational tables, keys, principles
SQL
reorganize cast/melt (pivot?)*
joining
times tidy data won't do well: things with matrices, summary tables, corpora, nested stuff, graphical models with nodes old models
tidy
plyr
reshape2
merge*
making univariate plots (ggplot2)
layers in ggplot2
bivariate plots in ggplot2
multivariate plots in ggplot2
adding a third variable
facets
jittering and opacity
color in ggplot2, linetype, size
mapping color or size
plot labels and clarity ggplot2
levels and keys
advanced plots
maps
text clouds
http://gallery.htmlwidgets.org/
https://www.r-graph-gallery.com/
graph/network diagrams
https://www.r-graph-gallery.com/
interactive plots
shiny Apps
reproduceable research and R markdown*
pretty things in R markdown
rmarkdown pdfs
projects
analysis
inference
CIs, t-test
linear regression
glm
lmm? glmm?
chi sq
predict
decision trees
clustering
hypothesis generate
future: programming with R
for loop
functions
installing R and R studio
install packages
class tutorials*
funtions, help, putting things in the function
get data in 1
get data in 2
get data in 3, reads in the wrong type, missing header, not lining up, excel, specialty SPSS, etc.
Objects in R (data frame, looking at them) access of column, head, View, summary, tibbles, store a new thing
data types date, dbl, int, char, num
Objects in R 2: lists, arrays, matrices
Using R Studio broom, running a line of code, open a script, look at things in the console*
bivariate summary statistics (lm, cor, two way table) 1
summarizing data by group*
mutate (create a new variable by group)*
create new variable and plot it
dealing with dates and times
dates and times in ggplot2
writing math
changing the look of a ggplot (themes)
bivariate plots in base
adding lines/points in base
color in base/pch/lty
interactions
logic in R
logic + sumstats
univariate summary stats (length, sum, summary, mean, median, quantile, IQR, table, prop.table, exclude null)
choosing plots to answer a question and 2d sum stats to answer a question
bivariate
Data analysis will be determined by the scientific question and the type of data
pipes
text processing
strings2
BI
tableau
Question types (hypothesis generate, estimate, predict, describe), what can be concluded - exp/obs study *
writing a file
one sample inference, weighted samples (one sample prop, one sample mean)
two variables, inference, tests from 220 two means, chi sq, lin reg,
additional 2 variable stuff that you probably didn't learn in 220 two prop diff, ANOVA
matched pairs - long and wide formats
correlated data methods
pick one of:
advanced plotting methods using leaflet, d3, maps, etc.
advanced data analysis methods (lmm,CART, clustering)
tableau or BI
future: webscraping
saving a plot
fancy ways to save plots
distributions, sampling
custom colors
Choosing plots for more than bivariate
vector calculations. +/-/*, ln, exp, ^, cumsum, lead, lag, diff create a new variable that is a transformation of an old variable
missing values, is.na
strings example of ordering : "V104" "V51" "A" "a" "0a"
creating a categorical variable from a continuous one
factors/reordering factors renaming factor levels, removing a factor level adding a level to a factor, converting factor to character to numeric
univariate base graphics
plot labels in base
subsetting data/ ordering data in base, seq, 1:10
subsetting data in tidyverse: filter, select, arrange
subset/reorder for plots or tables