SPSS is a statistical software package used for data analysis in business research that was originally developed for social science applications. It allows users to import, organize, and analyze data using a variety of statistical procedures and can generate reports, charts, and output. SPSS has evolved over time and is now owned by IBM, with capabilities including importing data from various sources, descriptive statistics, advanced statistical analyses, and command syntax for repetitive tasks.

1. INTRODUCTION TO
SPSS
Suresh T S
I M.Com
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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.

5. Now the company is known as
SPSS: An IBM® Company
:

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. Types of variables
 Independent Variable
 Dependent Variable
 Moderating Variable
 Extraneous Variable
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11. 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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12. 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

13. 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

14. 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
Primary Scales

15. Choice of Scales in SPSS
 The default is Scale, which refers to an
interval or ratio level of measurement.
 Choose Nominal for categorical data,
 Ordinal if your data involve rankings, or
ordered values.
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16. TYPES OF WINDOWS
Data view
Variable View
Output Viewer
Pivot Table Editor
Chart Editor
Text Output Editor
Syntax Editor

17. Data Viewer
Entering
Editing
Displaying
DATA
No. of Respondents/Questionnaires/Schedules

18. Variable View
Programming
Defining
Qualitative
Questions
Number of Questions

19. 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

20. Pivot table Editor
Text Edit

21. Double
Click
Editing
Options
Chart Editor

22. Syntax

23. 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.

24.  Gender
 Age
 SA ,A ,N ,DA, DSA