Getting ability to use SPSS

1. TRAINERS : BIZIMANA Appolinaire
HABINSHUTI Cyprien
IMANISHIMWE Valentine
December,06.2014

2. PART I: Introduction to SPSS
1.1 Background and objectives
1.2 Definition
1.3 Use of SPSS
PART II: Dealing with SPSS
2.1 Getting started with SPSS
2.2 Getting meaning of key terms
2.3 Creating code book
2.4 Data entry
PART III: Data management
Data analysis using SPSS

3. 3.1 Exploratory analysis
3.2 Descriptive analysis
3.3 Inferential analysis
We all invited to be part of SPSS user properly
Profiter l’occasion s’il ya du temps

4.  SPSS Stands for Statistical Package for Social Sciences
it had been specialized in data mining and statistical analysis
but also designing computer program for statistical analysis
and medical research , political science, administration, health,
etc.
 It is powerful and easy-to-use software program for data
manipulation and data analyses.
 it is designed primarily for the researcher or statistician.
Essentially, if you need to use this program, you will need to
learn basic statistics and its application before using this
program.

5.  The first version of SPSS appeared on the market way
back in 1968 original meaning of the abbreviation SPSS
is Statistical Package for the Social Sciences, but in its
present form SPSS is much more than that
 Since 1968 when SPSS was introduced as statistical
analysis program for social sciences
 At that time SPSS was used in psychology research to
analyze social research data. To day, however, SPSS is
usually used in business, market .

6. • By definition SPSS is orginally it is Statistical
Package for Social Science but now it stands for
Statistical Product and Service Solutions.
• SPSS is a data management and statistical
analysis tool

7. • Creating data entry matrix and datasets and managing
datasets
• Generating routine frequency tables, descriptive
statistics, distribution of multiple-choice question
responses etc.
• Creating graphical presentations of data for reporting,
presentations or publications
• Exploring relationships between variables using linear
and non-linear models
• Transforming variables or creating new variables from
existing ones

8.  Open up SPSSA
 Screen will pop up that has 5 different options to choose from as
follows

9. • Type in data – This will be the most commonly used
option. If this is selected, you can type in the data
manually.
• Skip Run an existing query, and Create a new
query using Database Wizard
• Open an existing data source – Like the name
implies, you can open a file that already has data in it from
this option.
• Select Type in data

11.  At the bottom of the page there are two tabs:
Data View and Variable View. The variable
view brings you to the page where you can enter
the variables into the program. For example if you
have a range of age groups, this is where you
would enter the age groups and their numerical
assignments. The data view is the tab where you
enter the raw data into the program.

12.  Open the file accidents.sav from
SPSS/Tutorial/sample_files/accidents.sav. You can
see an example of how these tabs work by playing
with them. If you look at the variable view tab, you
can see that there are 4 variables. If you click on the
data view tab, you can see these four variables at
the top of the work-area. A confusing aspect to
SPSS is that the rows in the variable view are the
columns in the data view tabs

13. Data View

14.  variables in variable view; each one has an
abbreviated name (with no spaces) that will show up in
the data view tab in place of the var that usually shows
up.
 The Label column is the full name of the variable, which
you can enter in as well with spaces. Under the Values
column, you can determine what numerical values
represent certain data points.
 For example, in the accidents.sav file, you can see that a
1 represents a female, and a 0 represents a male
 In the Scale column, this is where you determine the
type of data being used

15.  . For example, gender is a categorical type of
variable, so it best fits into the nominal option.
Furthermore, age category is an ordinal variable, so
the ordinal option would fit best.
 Nominal: A type of data classification that
categorizes data either by name or category.
Example: Hair color is “Brown” = Br, “Black” = Bk,
“Red” = Rd, and “Blonde” = Bl
 Ordinal: A type of data classification that categorizes
data by some order or rank. Example: “agree” = 3,
“somewhat agree” = 2, “does not agree” = 1

16.  In the data view tab, notice a small button that
looks like a price tag with a red end .If you click on
this button, it changes the data from numbers to
labels. You can see here that Females are
denoted with a 1 and males are denoted with a 0
as stated in the variable view. This makes
entering data into the work-area easier. Instead of
writing female for all of your data, you can just
enter a 1 and the program knows to treat it as
female.

17. Entering Data
Open up the variable view tab
You must first assign every variable a numerical
value
. For example assign a 1 to “Under 21” and a 2 to
“21-25” and a 3 to “26-30”.
This is the ONLY way for SPSS to quantify your data
Additionally it is advised to at least determine the
Label, Values, and Measure of your data.

18.  Column 1: Variable name
Short name: some characters are not
accepted to be used (better use letters
and numbers)
Column 2: Variable type
Numeric
Date
String

19.  Column 3: Width
Number of characters
 Column 4: Decimals
Number of decimals to be displayed
 Column 5: Labels
Description of the variables
 Column 6: values
List of possible values for discrete or
qualitative variables

20. Column 7: Missing
Codes for missing values
Column 8: columns
Number of columns booked for the variable
Column 9: alignment
Centered, left or right alignment
Column10: measure
Nominal: name, marital status, race
Ordinal: economic classes: very poor, poor, not
poor, rich, very rich

21.  It uses with you question in specification of your
variables
 Create your hand writing notes
 Associate the variable with some numbers
 It facilitate data entry

23.  After you have entered in all your variables, you
need to enter the data into the work-area. You
must now numerically assign your data sources.
For example, if you have taken a survey of 6
people (each person is a data source), each
person should be assigned a number of 1
through 6 on paper that will correspond to rows
in SPSS. This allows SPSS to correlate data
from each data source (i.e. what people
responded with what data).

24.  Each data set can then be assigned to its
respective row. This means that data
source 1 (the first person surveyed) will be
entered in row 1, and data source 2 will be
entered in row 2 and so on.

25. a. If the Value Labels button is pressed, you can
simply select to response of each survey from a
drop down menu in each cell. This can be done if
the cell that corresponds to the correct data
source (row) and variable (column) is selected
b. If the Value Labels button is not pressed, you
must enter the data in as a number (with no drop
down menu)

26. Figure 1 Figure 2

27. The Output window is a window that is separate from
the main window which shows you the results of
your analysis. For example, if you want to have a
graph of some of your data, it will pop up in the
output window.

28.  The area on the left is a log of all the data you
have generated in your study. The area on the
right is the visual output of that data
 For example, if you have 5 different graphs you
have made, you can click on any specific chart in
the left area, and it will appear (selected) in the
right area.
 If you look at the above figure , you can see that
the Log portion is selected, and it highlighted the
log data in the right section.

29. Manual Exercises to be done in Class
and making sure that every is able to
do the steps recursively

30. To save the data file you created simply click „file and‟
click
„save as. You can save the file in different forms by‟
clicking “Save as type.