Introduction to Statistics (MAT/SST 115.03 2008S)
Primary: [Front Door] [Syllabus] [Current Outline] [R] - [Academic Honesty] [Instructions]
Groupings: [Applets] [Assignments] [Data] [Examples] [Handouts] [Labs] [Outlines] [Projects] [Readings] [Solutions]
External Links: [R Front Door] [SamR's Front Door]
You will need to create a data frame (or two vectors) in order to do the analysis. Here's a start.
RNCtemps = data.frame(Month=1:12, AvgTemp = c(39, 42, ...))
You can load the data from the file Solitaire.csv.
One nice thing about R's cor is that, when given
a data frame as a parameter, it computes all the pairs of correlation
coefficients.
cor(Solitaire)
You can load the data from the file Climate.csv.
We can once again take advantage of R's willingness to compute simultaneously lots of correlation coefficients. However, this time we need to throw away one column (the city names). So, we need to coefficients for columns 2-9.
Climate2 = Climate[,2:9]
You should be able to figure out the rest.
Primary: [Front Door] [Syllabus] [Current Outline] [R] - [Academic Honesty] [Instructions]
Groupings: [Applets] [Assignments] [Data] [Examples] [Handouts] [Labs] [Outlines] [Projects] [Readings] [Solutions]
External Links: [R Front Door] [SamR's Front Door]
Copyright (c) 2007-8 Samuel A. Rebelsky.
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