Statistical Software

Ten Ways Learning a Statistical Software Package is Like Learning a New Language

January 31st, 2014 by

Someone recently asked me if they need to learn R.  In responding, it struck me that this is another way that learning a stat package is like learning a new language.

The metaphor is extremely helpful for deciding when and how to learn a new stat package, and to keep you going when the going gets rough. (more…)


R Is Not So Hard! A Tutorial, Part 11: Creating Bar Charts

January 28th, 2014 by

Let’s create a simple bar chart in R using the barplot() command, which is easy to use.

First, we set up a vector of numbers. Then we count them using the table() command, and then we plot them.

The table() command creates a simple table of counts of the elements in a data set.

H <- c(2,3,3,3,4,5,5,5,5,6)

Now we count the elements using the table() command, as follows: (more…)


Do I Really Need to Learn R?

January 23rd, 2014 by

Do I really need to learn R?

Someone asked me this recently.

Many R advocates would absolutely say yes to everyone who asks.

I don’t.

(I actually gave her a pretty long answer, summarized here).

It depends on what kind of work you do and the context in which you’re working.

I can say that R is (more…)


R Is Not So Hard! A Tutorial, Part 10: Creating Summary tables with aggregate()

January 21st, 2014 by

In Part 10, let’s look at the aggregate command for creating summary tables using R.

You may have a complex data set that includes categorical variables of several levels, and you may wish to create summary tables for each level of the categorical variable.

For example, your data set may include the variable Gender, a two-level categorical variable with levels Male and Female. Your data set may include other categorical variables such as Ethnicity, Hair Colour, the Treatments received by patients in a medical study, or the number of cylinders in motor vehicles.

In any case, you may wish to produce summary statistics for each level of the categorical variable. This is where the aggregate command is so helpful. (more…)


Using Python with SPSS

December 9th, 2013 by

by Lucy Fike

We know that using SPSS syntax is an easy way to organize analyses so that you can rerun them in the future without having to go through the menu commands.

Using Python with SPSS makes it much easier to do complicated programming, or even basic programming, that would be difficult to do using SPSS syntax alone. You can use scripting programming in Python to create programs that execute automatically. (more…)


R Is Not So Hard! A Tutorial, Part 9: Sub-setting

December 2nd, 2013 by

In Part 9, let’s look at sub-setting in R. I want to show you two approaches.

Let’s provide summary tables on the following data set of tourists from different nations, their gender and numbers of children. Copy and paste the following array into R. (more…)