plots and tables Flashcards
1
Q
why use tables and plots
A
- plots and tables allow us to convey a lot of information using relatively small amounts of space
- they structure the information we’re communicating so that it’s easier to understand than a wall of text
- good tables and plots are simply #aesthetic
2
Q
when to use tables and plots?
A
- tables and plots are not just for reports
- they are a good way of exploring data before analysis in order for us to get to know them
- not all plots and tables we create should be put in reports/papers
- if we are including them in reports/papers, they should be used to convey important information that would be cumbersome to convey in body text
3
Q
tables
A
- tidy way of presenting a lot of numbers
- a good table should be easy to read, well-organised and clear
- good for exploring and summarising data, and presenting results
4
Q
table - structural elements
A
- number - all tables should be numbered and the number should be referenced in paper/report
- title - should be descriptive
- header - clearly indicates what the data in each column mean
- body- logically organised into rows and columns
- note - optional, provides additional information necessary to correctly interpret data in the table
5
Q
types of tables
A
- frequency table
- grouped frequency table
- summary table
6
Q
plots
A
- sometimes, a picture is worth a thousand words
- great for communicating information about data that takes a lot of space to explain in writing
- good graphics should be both clear and packed full of information
7
Q
plots - structural elements
A
- number - all plots should be numbered and the number should be referenced
- title - should be descriptive
- axes - clearly labelled, with sensible ticks along them, and units of measurement
- graphics - clear, well designed, good size
- legend - if graphical elements are used to distinguish levels of variables, legend must be provided
- note - optional, provides additional information necessary to correctly interpret the plot.
8
Q
frequency plots
A
- good for exploring distributions of data
- they are intended for you, the analyst, not for the readers of your paper/report
- they can be nice but take up too much space, use up too much ink, and convey too little information
9
Q
histogram
A
- useful for plotting distributions of continuous variables only (interval and ratio)
- data need to be binned; width of individual bins is our decision, explicit or implicit
10
Q
density plots
A
- for continuous variables only
- simulate what a histogram with infinitely narrow bins would look like
11
Q
bar charts
A
- visualise distributions of categorical data (nominal and ordinal)
- they are still used for summarising data, so you’ll see a lot of them
- even the APA website shows them in their list of sample figures
- but when you’re drawing your own plots there are better choices
- colour isnt necessary here, but it’s at least meaningful
- sometimes it makes more sense to flip them horizontally
- grid lines can help comparing things in all kinds of plots
12
Q
summary plots
A
- unlike frequency plots, their primary aim is to summarise the data in terms of key statistics
- they are often used to compare variables across groups
- some of them can be used to gauge differences between groups and relationships between variables
- they are not a substitute for data analysis
13
Q
types of plots
A
- box plot - aka box-and-whispers plots
- grouped box plots
- violin plot
14
Q
errorbar plot
A
- errorbar plots are great for showing means and spread/inferential statistics
- some of them can be used to gauge statistical differences between groups
- error bars can show several things (e.g., standard deviations, standard errors, their multiples)
- plot should clearly indicate what they represent
- pay attention to what the error bars mean
- interpretation of plots changes based on what the bars show
15
Q
scatter plot
A
- best way to show relationships between two continuous variables
