Technology has given us lot of convenience over almost every day to day task and it’s good to take advantage of it. I’m going to explain how to use a free statistics software to get most of your statistics analysis done pretty easy. Now, l’m not actually explaining concepts in statistics but l think it’s good to give a general idea about what statistics deals about. Most often, the science of statistics frighten most of us who lacked mathematics background but it’s not actually that bad if you pay attention to the concepts and get your algebra skills together. Statistics is the science of collecting, describing and interpreting data. Statistics is used in almost every field in life. For example, polls, news, journals, magazines etc. When you hear a statement like, majority of people living in the United States are white, that’s statistics at work. There are two areas of statistics;Descriptive statistics and Inferential Statistics. Descriptive Statistics is summarizing or describing a set of data. Inferential Statistics is the method of drawing conclusions about population based on a sample. Ok, there are lot of terms in statistics, the earlier you grasp the meaning and concept behind these words, the better your chances of understanding what is going on in statistics. Some of the terms you will hear on day to day basis in statistics are population, sample, data, census, etc. Now, when you collect data in a sample like the height of students in your class, this data can not easily give you the full explanation behind what you have collected until you analysed it using any of the statistical methods of analyzing data. Graphs are the most important tools used by statisticians in analyzing data. There are different types of graphs and the one to use depends on what type of data under investigation. I think it’s good to mention that there are two types of statistical data; qualitative and quantitative. Qualitative data is a non-numerical categorization type of data, example gender. Under Qualitative data, we have Nominal and Ordinal Data. In short Nominal Data only describes the categories of the data without any order, example eye color, gender. We can’t say one gender is better than the other without adding more information to the data. Ordinal data is the qualitative data that is ordered, example is grade (A>B>C>D>F). Quantitative Data is the numerical type of data. There are two types, Discrete and Continuous. Discrete Data can be counted example number of children, Continuous data is measured on a continuum, example time, weight etc.For analysis, statisticians use many tools especially graphs to analyse and interpret the data. There are different types of graphs, histograms, bar charts, pie charts, leaf and stem display, Box chart etc. The type of graph you use to analyse the data depends mostly on the type of data. It’s a good advice to read more on these types of graphs to know which one to use at the right time. Now lets go on and state the procedures for obtaining free R and R Commander package, a statistical software that you can use to analyse almost every type of data you’ve collected. It has all the graphs available so it’s all up to you to know which graph to use for your data. Below are the steps:
Installing R and R Commander(Rcmdr)
For Windows:
Install R first:
1. Go to http://www.r-project.org/
2. On the left under “Download, Packages” select CRAN (Comprehensive R Archive Network).
3. Select any of the CRAN links listed (United States are on the bottom of the page).
4. Select Download R for Windows.
5. Select base.
6. Then, click on Download R 2.13.1 for Windows, save the file (R‐2.13.1‐win.exe) somewhere on
your computer .
7. Run the EXE‐file and follow the instructions.
Once R is installed, you have to load the Rcmdr package using the following steps:
1. Start R.
2. At the prompt enter the following command: install.packages(“Rcmdr”,
dependencies=TRUE)
3. After the installation is finished, you can start the Rcmdr by typing library(Rcmdr)
For Mac:
Install R first
1. Go to
2. On the left under “Download, Packages” select CRAN (Comprehensive R Archive Network).
3. Select any of the CRAN links listed (United States are on the bottom of the page).
4. Select Download R for MacOS X.
5. Select R‐2.13.1.pkg and save the file somewhere on the computer.
6. Double click on the file and follow the instructions.
Once R is installed, you have to load the Rcmdr package using the following steps:
1. Go to the http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/installation‐notes.html and scroll down
to Mac OS X and follow the instructions to download tcltk‐8.5.5‐x11.dmg, then start R.
2. At the prompt enter the following command: install.packages(“Rcmdr”,
dependencies=TRUE)
3. After the installation is finished, you can start the Rcmdr by typing library(Rcmdr)
For more information on Rcmdr you may also check out: http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/
After you have R and Rcmdr working on your system, lets see how we can use it to analyse a data set. The best way to provide the data set to be analysed by the software is to type the data in notepad or excel. Save it on your computer, then start R and import the data from your computer into R for analysis.
Creating the file containing the data set.
1.Open notepad on your computer
2. In the first line of your file enter the variable names. Each variable name should only be one word. Make sure to separate each variable name by the same symbol. I recommend Tabs, but you may also use spaces or commas.
3. Then, start a new line for each subject and separate the values by the same symbol you used for the variables (i.e. Tabs, spaces or commas). (see example below for a sample Tab-delimited file)
Once you are finished entering the data, save the file as a TXT-file in your preferred directory.
Now, you can import the file into R for analysis. here are the steps;
1. Start R by clicking the icon or through programs in your start menu of the computer
2. When R starts up, type at the prompt library(Rcmdr) and press enter.
3. The R commander window will load up and show as a separate window on the R window.
4. In the R commander window, click on Data in the top menu bar.
5.A drop down menu list shows, point the mouse to import data and move the mouse over to the right and select from the menu list that show the following: from text file, clipboard or URL.
6. A new small window shows to specify the properties of the text file. In that window, you enter a name to describe your data set( always use one word for the name). Then check the box next to variables in file if you put your variables in the file as show in the demonstration file below. The next thing in the window is to type what you use to represent missing values in the file. You can leave that to have the default NA or enter what you used to denote missing values, if they exist in your data. Then check local system as the location of the file. Select the type of separator used for your values, if you use tab, check tabs, if you use white space or comma, check it. Remember to be consistent with your separator during file creation. you can mix it up. If you start using tabs to separate your values, you must stick to it for the entire file. Then you select the symbol for decimal points if they exist in your file. After all these procedure, click on the Ok button.
7. A directory listing browser shows up, navigate to where you stored the text file for the data and click on it to load it to R commander.
8. Once your data is loaded successfully, you can perform the analysis you want to do. For example, if you want to draw histogram, just click on graphs from the top menu and select histogram from the drop down menu that show. R commander will show up a window where you choose the variables to use in drawing the histogram, select it and click Ok to draw the histogram. A new window will show with the graph in it. You can draw different graphs using the same data but any time you draw a new graph, the previous graph is replaced with the new one in the window.
Demonstration File: ID represents some apartments, S-room refers to number of single rooms in the apartment, D-room represents number of double rooms in the apartment.
ID S-room D-room
1 50 79
2 1800 54
3 3333 74
4 2283 62
5 4533 85
6 2883 55
7 4700 88
8 3600 85
9 1950 51
10 4350 85
This is the simplest way. If you have a spreadsheet program (like Excel), you can enter the data probably more conveniently. Just make sure, you save it as a TXT file (or some other compatible format).
