plotting

R is Not So Hard! A Tutorial, Part 22: Creating and Customizing Scatter Plots

December 31st, 2015 by

by David Lillis, Ph.D.

In our last post, we calculated Pearson and Spearman correlation coefficients in R and got a surprising result.

So let’s investigate the data a little more with a scatter plot.

We use the same version of the data set of tourists. We have data on tourists from different nations, their gender, number of children, and how much they spent on their trip.

Again we copy and paste the following array into R.


T <- structure(list(COUNTRY = structure(c(3L, 3L, 3L, 3L, 1L, 3L, 2L, 3L, 1L, 3L, 3L, 1L, 2L, 2L, 3L, 3L, 3L, 2L, 3L, 1L, 1L, 3L,
1L, 2L), .Label = c("AUS", "JAPAN", "USA"), class = "factor"),GENDER = structure(c(2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L), .Label = c("F", "M"), class = "factor"), CHILDREN = c(2L, 1L, 3L, 2L, 2L, 3L, 1L, 0L, 1L, 0L, 1L, 2L, 2L, 1L, 1L, 1L, 0L, 2L, 1L, 2L, 4L, 2L, 5L, 1L), SPEND = c(8500L, 23000L, 4000L, 9800L, 2200L, 4800L, 12300L, 8000L, 7100L, 10000L, 7800L, 7100L, 7900L, 7000L, 14200L, 11000L, 7900L, 2300L, 7000L, 8800L, 7500L, 15300L, 8000L, 7900L)), .Names = c("COUNTRY", "GENDER", "CHILDREN", "SPEND"), class = "data.frame", row.names = c(NA, -24L))


T
attach(T)

plot(CHILDREN, SPEND)

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Linear Models in R: Improving Our Regression Model

April 23rd, 2015 by

by David Lillis, Ph.D.Stage 2

Last time we created two variables and used the lm() command to perform a least squares regression on them, and diagnosing our regression using the plot() command.

Just as we did last time, we perform the regression using lm(). This time we store it as an object M. (more…)


Linear Models in R: Diagnosing Our Regression Model

April 21st, 2015 by

by David Lillis, Ph.D.Stage 2

Last time we created two variables and added a best-fit regression line to our plot of the variables. Here are the two variables again. (more…)


Linear Models in R: Plotting Regression Lines

April 10th, 2015 by

by David Lillis, Ph.D.Stage 2

Today let’s re-create two variables and see how to plot them and include a regression line. We take height to be a variable that describes the heights (in cm) of ten people. (more…)


R Graphics: Plotting in Color with qplot Part 2

January 13th, 2015 by

by David Lillis, Ph.D.

In the last lesson, we saw how to use qplot to map symbol colour to a categorical variable. Now we see how to control symbol colours and create legend titles.
(more…)


R Graphics: Plotting in Color with qplot

January 12th, 2015 by

by David Lillis, Ph.D.

In this lesson, let’s see how to use qplot to map symbol colour to a categorical variable.

Copy in the following data set (a medical data set relating to patients in a randomised controlled trial):

(more…)