INTRODUCTION TO SPSS

Suresh T SI M.Com314

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 Questionnaireso Reporting in Tables and Graphso Analyzing: Means, Chi-square, Regression, …and much

more..

HistorySPSS 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.

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.

Now the company is known as

SPSS: An IBM® Company :

General CapabilitiesSPSS 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.

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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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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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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Types of variables

Independent Variable

Dependent Variable

Moderating Variable

Extraneous Variable

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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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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

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Nominal Numbers

Assigned to Runners

Ordinal Rank Order

of Winners

Interval PerformanceRating on a Scale

Ratio Time to Finishin Seconds

Thirdplace

Secondplace

Firstplace

Finish

Finish

8.2 9.1 9.6

15.2 14.1 13.4

Scale

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 ScalesPrimary Scales

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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TYPES OF WINDOWS

Data view

Variable View

Output Viewer

Pivot Table Editor

Chart Editor

Text Output Editor

Syntax Editor

Data Viewer

Entering

Editing

Displaying

DATA

No. of Respondents/Questionnaires/Schedules

Variable View

Programming

Defining

Qualitative

Questions

Number of Questions

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

Pivot table EditorText Edit

Double Click

Editing Options

Chart Editor

Syntax

Manually Entering DataSPSS 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.

Gender Age SA ,A ,N ,DA, DSA