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Summary R Code Cheat Sheet
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Summarized codes and lecture notes for LFE763 (Statistics for Biological Research)
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R-Codes,
, NB: REMEMBER TO SET WORKING DIRECTORY
Data Visualization – Example Data: Census
Tufte’s 6 Principles of Graphical Integrity
1. Representation of numbers should match the true proportions
a. The “lie factor’ is a value used to describe the relation between the size of effect
shown in a graphic and the size of effect show in the data
b. Lie factor = size of effect shown in graphic/actual effect in data
c. Normally aim for a life factor 0.95 – 1.05
2. Labelling should be clear and detailed.
3. Design should not vary for some ulterior motive, show only data variation.
4. To represent money, well known units are best
a. Dollars or Pounds
5. The number of dimensions represent should be the same as the number in the data
a. Eg: Use are to show one dimensional data
6. Representations should not imply unintended context
Import Data: IceCream <- read.csv (“file name”)
View Data: View (IceCream)
Headers: Head (IceCream) – see the headers
Summary: summary (IceCream – summary of statistics of each column within the
data
Select Specific Column: IceCream $ColumnName
Maximum Value: max(IceCream $ColumnName)
Minimum Value: min(IceCream $ColumnName)
Range: range(IceCream $ColumnName)
To test for normality:
Subset: subset(filename, column name = “data of interest”
o Subsetting two variables: subset1 < - subset (filename, x1 == “a” & x2 ==
“b”
o Where the value “a” is one subset of the values in variable x1 and the value
“b” is one subset of the values in variable x2
Transforming Data & Adding Data
IceCream $ColumnName_transf <- (IceCream $ColumnName)^5 – Raises data to the
power of 5
IceCream $ColumnName_transf <- exp(FileName$ColumnName) – Raises the
constant e to the power of the population
IceCream$ColumnName_transf <- (IceCream $ColumnName) * 10 – Multiplies data
by 10
Log Transformations
Log(IceCream$ColumnName) – Computes log base e of data
Log(IceCream$ColumnName, 2) – Computes log base 2 of data
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