fundamental to spss

8/12/2019 Fundamental to SPSS

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INTRODUCTION

DATA VIEW

VARIABLE VIEW

SCALING

OUTPUT WINDOW



SPSS stands for “Statistical Package for the Social Science” which was latterchanged to “ Statistical Product and Service Solution” and now just SPSS

representing a Chicago based firm which owns this statistical package

This software was initially created by three Stanford graduate student in 1960’s

Key features of SPSS are

◦ More comprehensive then windows

◦ More user friendly then SAS

Key steps to open SPSS window

STARTALL

PROGRAMS

MENU

FOLDER

SPSS 14.0FOR

WINDOWS

OPEN NEWWINDOW



Menu Commands

Toolbar icons

Subject or case

number

Click here to

name first variable

Empty data cells

Scroll bars

Data view, variable

view tabs



File: Deals with different functions associated with files including opening, reading,

saving and exiting SPSS

Edit: A number of editing functions including copying, pasting, finding and replacing View: Several options that affect ways of screen appears, most frequently used is

Value label

Data: Operations related to defining, configuring, entering data also deals in sorting

cases, merging or aggregating files and selecting or weighting cases

Transform: Transformation of previously entered data include recording, computing,

new variables, reordering and dealing with missing values

Analyze: All forms of data analysis like tables, t-test, regression, reports, compare

means, etc.

Graphs: creation of graphs or charts with this option

Utilities: Utilities deals largely with fairly sophisticated ways of making complex data

operations easier

Add-ons: Option to buy advance software and add to basic software

Windows: Deals with the position, status and format of open windows

Helps: Include search capabilities, tutorials and statistics coach



Specification of

each variable

Name

Type

Width

Decimal

Label

Value

Missing

Columns

Align

Measure orscale



Three type of scale are prominently used in SPSS which are mentioned below

Scale: Scale have intrinsic numeric meaning that allow typical mathematical

manipulations. Key types are years, quizzes, final score, etc.◦ For Example, age is a scale variable: 16 is twice as much as 8

Ordinal: Measures have intrinsic order but mathematical manipulation are typically

meaningless

◦ Key example like male/female, true/ false, pass/fail

Nominal: Measures used for identification but have no intrinsic (lesser to greater)

order such as ethnicity, marital status, and alphabetical strings variables

◦ Nominal data is used for categorization but not used for analysis

fundamental to spss

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