It is critical to get your data entered and set up correctly in SPSS to be sure that you will work quickly and efficiently.
When importing or entering data the rule to remember is as follows: All the information about one thing does in one row, or to expand it a bit information about different things goes in different rows (and the same column) whereas information, or data, about the same thing goes in different columns (and so the same row). 

So if you had a list of peoples' names and their heights, weights and ages then in the first column you would put the first person's name, in the second their height, in the third their weight and in the fourth their age. So all information about the same person goes in the same row but in different columns.

Obviously there are exceptions to this rule when you get to using SPSS and you have a variable that defines a group of things but if you're not absolutely sure you should always stick with the rule above.
 

The Variable View window in SPSS contains information about the data that you can see in the Data View.

In this post I will go through each of the column titles to explain little more about what that column is for. Remember that each column in the Variable View window refers to a piece of data in the Data View.

Name - As you can probably guess this is the name of the dataset. In SPSS each name must be unique and the first character must be alphanumeric. You are not permitted to have any spaces in this field.

Type - This column contains details of what type of data your data set contains. In the main most data falls into 2 or 3 categories - String, Numeric or Date- although there are others, for example dollar for currencies.

If you click on the Type box at the top of the column this will open a dialogue box that will allow you to quickly define the data type.

Width - This is just allowing you to define the maximum number of characters that can be entered for the variable. SPSS's default setting for this is 8.

Decimals - Obviously really, in SPSS this is limited to 16 or fewer. SPSS's default setting for this is 2.

Label - The name setting has some limitations and also needs to be kept relatively short as long names do not show in column headings. The label setting can contain a much longer description of the data which can be very useful, especially when sharing data.

Values - This is used to link numbers to categories where the variable represents a category. For example in some data you may sort between pensioners and workers by their age so that an OAP is a 1 and a worker is a 2. Values then allows 1 to show as an pensioner and 2 to show as a worker. 

Missing - This will tell SPSS what to do if there is a missing piece, or pieces, of data in the data set. Clicking on this column will bring up the Missing Values dialogue box which allows you to define the missing data. You may choose to have all missing pieces of data represented by one number - 999999 for example - or represent data that is missing for different reasons in different ways. An example of this would be if people have ignored or missed out a question they could be categorised as 999999, but if they've written Not Applicable they could be categorised as 888888.

Columns - This defines how wide the column is and so how many characters are displayed at the top of the column.

Align - This is the same as in Microsoft Office products and is left, centre or right.

Measure - Last but not least measure is where the way that the data was measured is recorded - so its either nominal, ordinal or scale.

Hopefully you'll find that helpful next time you're working through a Variable View in SPSS.

There are 4 main windows in SPSS and we thought it would be useful to introduce you to what the 4 windows in SPSS are and what each is used for:

1. Data View - The data view is used to store and show your data. It is much like an ordinary spreadsheet although in general the data is structured so that rows are cases and the columns are for the different variables that relate to each case.

2. Variable View - The variable view contains the variables on your data set, so it defines the properties of your dataset. Each row will define all of the various variables for one set of data. For example, for a numerical piece of data this would show (amongst other things) the number of decimal places that are stored for that piece of data.

The variables include - name, type, width, decimals, label, values, missing, columns, align and measure. Ensuring that the 'measure' of your variables is correct is vital. The variable can be Nominal which is for strings of data, Ordinal for data that isn't continuous but can be ranked or ordered or, finally, scale which is used for a variable that is continuous, for example a distance to somewhere.

3. Output Viewer Window - This window is used to show the results that have been output from your data analysis. Depending on the analysis that you are carrying out this may include the Chart Editor Window or Pivot Table Window.

4. Syntax Editor Window - This window shows the underlying commands that have executed your data analysis. If you are a confident coder this is where you can amend the code, or write your own from scratch, and then run your own custom analysis on your data set.

So there you have it, a whistle stop tour of the 4 main windows that you will find in SPSS.