2. What is SPSS?
Originally it is an acronym “Statistical Package for the
Social Sciences” but now it stands for Statistical Product
and Service Solutions It is also known by the name
PASW (Predictive Analytics Software)
It is a software used for data analysis in business research.
Can be used for:
o Processing Questionnaires
o Reporting in Tables and Graphs
o Analyzing: Means, Chi-square, Regression, …and much
more..
3. History
SPSS has a long heritage
Introduced in 1968.
Was originally developed to facilitate statistical
analysis in the social sciences.
Early versions designed to run on mainframe
computers.
On July 28, 2009 IBM announced it was acquiring
SPSS Inc. for $ 1.2 billion in cash
The current versions (2015) are officially named
IBM SPSS Statistics.
4. About SPSS Incorporated
SPSS Inc. is a leading worldwide provider of
predictive analytics software and solutions.
SPSS Inc. was a software house headquartered in
Chicago and incorporated in Delaware
The company was started in 1968 by Norman Nie,
Dale Bent, and Hadlai "Tex" Hull
Today SPSS has more than 250,000 customers
worldwide, served by more than 1,200 employees in
60 countries.
6. General Capabilities
SPSS has a lot of great features
Can import data from many different sources, such as
Microsoft® Excel and SAS®.
Provides analysis tools to generate reports, charts,
plots, descriptive statistics, and run advanced
statistical analyses.
In addition to user interface, provides a command
syntax that can simplify certain things, such as
running repetitive tasks.
7. Basic Operations in SPSS
(Basic Steps In Data Analysis)
Variable Entry (adding or deleting a variable)
Data Entry (adding or deleting the data)
Saving the data
Importing data from Excel file
Checking the data entered
Sorting the data
Transforming the data
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8. Variables
A concept which can take on different
quantitative values is called a variable.
Ex. What are variables you would consider in buying
a second hand bike?
Brand
Type
Age
Condition (Excellent, good, poor)
Price
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9. Dichotomous variables (having two values only)
Yes or No
Male or Female
Income, age or a test score are the examples of
continuous variables.
These variables may take on any value within a given
range, or in some cases, an infinite set.
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10. Measurement Scales
The process of assigning numbers to objects in such
a way that specific properties of the objects are
faithfully represented by specific properties of the
numbers.
Types of Scales:
Nominal
Ordinal
Scale
Interval
Ratio
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11. Types of Scales
Nominal
example: nationality, race, gender…
based on a concept (two categories variable called
“dichotomous nominal”)
Ordinal
example: knowledge, skill... (more than, equal, less than)
rank-ordered in terms of a criterion from highest to lowest
Interval/Ratio
example: age, income, speed...
based on arithmetic qualities and have a fixed zero point
12. 7 3
8
Nominal Numbers
Assigned
to Runners
Ordinal Rank Order
of Winners
Interval Performance
Rating on a
Scale
Ratio Time to Finish
in Seconds
Third
place
Second
place
First
place
Finish
Finish
8.2 9.1 9.6
15.2 14.1 13.4
Scale
13. Scale Basic
Characteristics
Common
Examples
Nominal Numbers identify
& classify objects
Gender,
numbering of
football players
Percentages,
mode
Chi-square,
binomial test
Ordinal Nos. indicate the
relative positions
of objects but not
the magnitude of
differences
between them
Quality rankings,
rankings of teams
in a tournament
Percentile,
median
Rank-order
correlation,
Friedman
ANOVA
Ratio Zero point is fixed,
ratios of scale
values can be
compared
Length, weight Geometric
mean, harmonic
mean
Coefficient of
variation
Permissible Statistics
Descriptive Inferential
Interval Differences
between objects
Temperature
(Fahrenheit)
Range, mean,
standard
Product-
moment
Primary Scales
15. TYPES OF WINDOWS
Data view
Variable View
Output Viewer
Pivot Table Editor
Chart Editor
Text Output Editor
Syntax Editor
16. Data Editor (.sav files)
The Data Editor lets you see and manipulate
your data. You will always have at least one
Data Editor open (even if you have not yet
opened a data set). When you open an SPSS
data file, what you see is a working copy of
your data. Changes you make to your data are
not permanent until you save them (click File -
Save or Save As). Data files are saved with a
file type of .sav, a file type that most other
software cannot work with
19. VARIABLE VIEW
In the Variable View you can see and edit the
information that defines each variable
(sometimes called meta-data) in your data set:
each column of the Data View is described by
a row of the Variable View.
23. 1. Opens automatically if it
runs a procedure
2. Displays Statistical results,
Graphs and save it for
future use.
Outline Pane
Navigate output
Highlight output
Pivot table editor
Text output edit
Chart Editor
27. Manually Entering Data
SPSS makes it easy.
Start with the Data Editor.
There are two tabs at the bottom:
Data View
Variable View
Gives you two ways to enter data:
Start with Data View and just start typing!
Start with Variable View and define your variables
first.
Think of variables as labels that describe your data.
