SPSS Assignment

Assignment-1
SPSS
Introduction to SPSS
What does SPSS stand for?

It basically stands for Statistical Package for Social Sciences. SPSS incorporated is a leading
worldwide provider of predictive analytics software and solutions.
SPSS is a Windows based program that can be used to perform data entry and analysis and to
create tables and graphs. SPSS is capable of handling large amounts of data and can perform
all of the analyses covered in the text and much more. SPSS is commonly used in the Social
Sciences and in the business world.
SPSS – first version was released in 1968, after being developed by Norman H. Nie, Dale H.
Bent and C. Hadlai Hull. The company was then acquired by IBM on 28 th July 2008 for US $
1.2 Billion. Between 2009-11 primer vender of the SPSS was called PASW (Predictive
Analytic Software). The latest version was released in the year 2012.
It is considered to the most popular statistical packages which can perform highly complex
data manipulations and analysis with simple instructions.
Uses of SPSS
It comes into picture after the data has been collected through various methods such as
questionnaires, etc. questionnaires would be coded and entered into SPSS as data. Questions
from the questionnaires are mapped into variables.
Things to keep in mind before data entry into SPSS:
Question- Response Format
 Close ended
 Open ended with numerical response
 Open ended with text response
 Multiple response questions
All these formats must be converted into numeric or string data before entering into SPSS.
Open-ended with numerical response
Ex. For how many years have you been registered as a student in Amity university?
------- year(s)
Data as such should be uploaded as it is.
Open-ended with text response
Ex. I would like to have the assortment extended of the following products:
_____________________
Processing:
Answers can be typed literally (text variable), or
manually coding afterwards.
Structuring data for use in SPSS

The way you lay out your data in SPSS will depend upon the kind of data you have and the
analysis you propose to carry out. However, there are some basic principles that apply in all
situations. 1 SPSS expects you to put each case on a row. Usually this means that each
research subject will have a row to their self. 2 Categorical variables are best represented by
numbers even if they are not ordered categories, they can then be ascribed a text label using
the "Variable Labels" option. 3 The variable name that appears at the top of the column in
SPSS is limited in length and the characters it will hold, the variable label can hold a more
meaningful description of the variable and will be used on output (graphs etc.) if you fill it in.
4 If you have two (or more) groups of subjects each subject will still have a row to their self,
however you will need to dedicate a variable (column) to let the system know which group
each subject belongs to. Examples of some typical data structures are below.
Two Independent Groups of data. (This structure would arise from what stats books might
call a between groups experiment.) These data were gathered as part of an investigation into
the effect of horse riding on balance. Sway area is a measure of balance, or more correctly,
unbalance, a small value indicates good balance. The variable called "rider" discriminates
between riders and nonriders, it can be referred to as a discriminatory variable. To set up a
“Value Label” to give meaning to this variable first, click on the “Variable View” tab at the
bottom of the data screen, second, in the variable view screen, notice that each variable now
occupies a row, and the columns represent the attributes of that variable, the rider variable is
numeric, 11 characters wide with no decimal places.
 Starting SPSS:
Click on the Start menu ( ) > All Programs > IBM SPSS Statistics > IBM SPSS

Statistics 21 (or whatever is the latest version number) to open the SPSS program.
When you first open SPSS on your computer, you should see something that looks similar to
following screenshot:
SPSS automatically assumes that you want to open an existing file, and immediately opens a
dialogue box to ask which file you’d like to open. It’ll make it easier to navigate the interface
and windows in SPSS if we open a file.
 Opening Data:
In the active dialogue box that asks very nicely, "What would you like to do?", we are going
to "Open an existing data source", by clicking the "More files ..." option and finding our way
to where we earlier saved our H&S dataset.
Once you have found the file you want to open, click Open and you’ll (hopefully!) see a data
file in front of you that looks something like this:
The other bit you may have noticed pop up was another window, mostly blank, but with a bit
of funny looking writing in it, like this:
Now that we have opened a data file, SPSS automatically opens what is called an “Output
Viewer” window. We’re going to talk about the SPSS interface, including this window,
shortly. Next, we have an example of how to open a data file using the SPSS drop down
menus.
It can be handy to know how to open a dataset once you’re already in SPSS, using the drop-
down menus.
So far, we've learned how to open an SPSS file when we first open SPSS. But sometimes
you might already have SPSS open and wish to open (another) data file. Later on, we will
talk about how to use syntax files to work in SPSS, starting with opening data, but for now,
here's how to open a file using the menus:
Click on the File menu at the top left of your Data Editor window, then Open > Data …:
Here you can navigate to your working folder and open your data file.
 Navigating the SPSS interface
Data editor window
This is the window where you can see your data, and information about the variables in your
dataset. It is also possible to change your data in this window, but I would strongly
recommend against ever changing your data that way because things can go terribly wrong,
and you have no record of what you changed and how you changed it!
There are two ‘views’ for the Data Editor window:
1) Data view – you can see the actual data in your dataset for each record and each variable;
and
2) Variable view – this gives a summary of each variable in your dataset, including the
variable name, type, various properties of the way in which the data are stored, any label(s)
for the variable itself and variable values (such as value labels for categories of sex, which in
the dataset may be represented as 1 and 2, relating to male and female).
 Syntax editor window
A second window in the SPSS interface is the Syntax Editor window. SPSS doesn’t
automatically open a syntax file for us, so let’s open one now. Click on the File menu in the
top left corner of your screen, and select New > Syntax:
The syntax window is where we can run commands (tell SPSS what we want it to do), such
as opening files, editing and managing data, undertaking statistical procedures and tests, and
saving files. The Syntax Editor window is essentially a file that we can use to record and
save everything that we do for a particular piece of analysis, or when managing/editing a
dataset. When you first open a syntax file, it looks similar to a blank Word document:
While many people feel extremely uncomfortable using syntax and would much rather use
the built-in menus (sound like you?!), in SPSS you can actually do both (use the menus and
the syntax file) for many procedures. We will start off by doing this, to ease you into using
SPSS syntax.
Regardless of whether you write the syntax yourself or paste it into a syntax file from the
menus, it really is best practice to use a syntax file to keep a record of all your data
management and analysis procedures.
van den Berg (2013) lists six reasons you should use SPSS syntax:
1. Syntax is ideal project documentation.

2. Syntax can be corrected.
3. Syntax can be recycled.
4. Syntax gets things done fast.
5. Typing syntax saves time; and
6. Syntax has more options.
 Output viewer window
Any time you do anything in SPSS – even just opening a file – SPSS will document it in the
Output Viewer window. If you don’t already have an output window open, SPSS will open a
new one for you, as it did when we first opened a dataset.
The output viewer window will keep a record of any and all commands you give SPSS (e.g.,
open a file, save a file, etc.), and is also the window in which you can view the results of any
data/statistical procedures undertaken. You can see in the screenshot below, that SPSS has
made a record in the Output file that you opened a particular SPSS file:
It shows us the syntax command that SPSS recognises to open a file (GET FILE), and it also
shows us the structure of the syntax:
GET FILE= ‘[file path\file name. Sav]’.
GET FILE is the command, then there is an equal’s sign (=), followed by the file path and
file name. Sav in single quotation marks, and a full stop (.) at the end of the command. SPSS
syntax always starts with the command name and always ends with a full stop (.).
The second line starting with the command DATASET NAME is a very useful piece of
syntax – we’ll get to that shortly!
Similar to the Syntax Editor window, the Output Viewer window is simply a file that you can
save and edit if you wish. You can also copy tables and graphs (or anything else) presented
in the output file into Microsoft Word, Excel, or other similar programs.
 Getting organised
When you’re working with data in SPSS (or any software for that matter), ideally you should
keep your work organised. How you organise your work is up to you, but here are some
general tips that may help make your life easier:
1. Keep all the files relating to a single ‘project’ in the one place. A ‘project could be
an analysis for a chapter of your thesis or for a publication, primary data collection,
data management processes, etc.
2. Make sure you work is backed up. Either save it somewhere that is automatically
backed up, or back it up yourself, regularly.
3. Never edit your original data file. You should always keep a copy of your original
data and keep it somewhere that you won’t accidentally edit or overwrite it. You may
want to keep it in a sub-folder, for instance. Sometimes we make mistakes in
managing and using data and need to go back to the original file. Storing your
original data can also be an important ethical consideration.
4. Label your files well, with descriptive file names.
o You may like to number them in the order that they occur in the project by
placing a number at the front of the filename (a good way to do this is to
number using tenfold (10, 20, 30 …) so that you can insert files later if
needed. For example, you could prefix a file with 15 if you wanted it to be
run between file 10 and 20.
o Use descriptive file names so that you have a good idea what’s in there when
you want to find something a year or two (or five) down the track.
 Organise your SPSS files
If you have never been so organised with your data sets, now is an excellent time to start!
There’s really not a whole lot worse than doing a bunch of analyses using multiple datasets
and having the files all jumbled in with other documents … or worse, spread all over the
place in separate folders!
1. Select a location on your computer, removable disk drive, or a cloud location to

organise your files for this workshop.
2. Use some of the tips above to label your files well and save original data in a sub-
folder (you can take copies of the original data files and save them in the main folder
location).
Your folder might now look something like this:
Note: the “original data” folder has a copy of all datasets (in SPSS and Excel) shown in this
main folder directory.

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Assignment-1

What does SPSS stand for?

Structuring data for use in SPSS

Click on the Start menu ( ) > All Programs > IBM SPSS Statistics > IBM SPSS

 Syntax editor window

1. Syntax is ideal project documentation.

GET FILE= ‘[file path\file name. Sav]’.

1. Select a location on your computer, removable disk drive, or a cloud location to

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