The document introduces SPSS as a powerful statistical package for social sciences that streamlines data analysis and manipulation. It covers basic statistical concepts, types of data, sources of data, and the functionalities of SPSS including data entry, editing, and various statistical techniques like correlation and hypothesis testing. Additionally, it discusses levels of measurement and provides insights into questionnaire design and data output features in SPSS.

4. INTRODUCTION
TO
S P S S

5. STATISTICAL PAKAGE FOR SOCIAL SCIENCE
STATISTICAL PRODUCT AND SERVICE SOLUTION
NOW

6. Why we use SPSS???
• SPSS makes our work easy and save our
precious time
• SPSS presents best tabulated and graphical
output
• SPSS helps the users to analyze and
manipulate the data within seconds.

7. • Basic concepts of statistics
• Sources of data for research
• How to Use data in SPSS???
• Description and practical of entering and editing
statistical data in SPSS.
• Basic concept of measuring scales
• Analysis and manipulation of data in SPSS
• Questionnaire Design and SPSS
• Descriptive statistics and frequency distribution in SPSS
• Correlation and Regression techniques in SPSS
• Testing of hypothesis t-test and z-test in SPSS

8. What is statistics???
The branch of science which
deals with the collection ,
organization ,summarization,
analysis and interpretation of
data.
Basic concepts of statistics

9. DESCRIPTIVE STATISTICS
It deals with the collection,
classification ,summarization
and presentation of data.
INFERENTIALSTATISTICS
It deals with the making
inferences about population
parameter on the basis of
sample information or data.
Basic concepts of statistics

10. SAMPLE: A representative part of population
STATISTIC: A numerical value get from sample
POPULATION: A well-defined group of data
PARAMETER: A numerical value get from population
Basic concepts of statistics

11. Statistical data or simply
data are the observations
or recorded values of our
interest.
Basic concepts of statistics

12. QUANTITATIVE DATA
Variable which we can
measure is Quantitative data.
Example:
Height ,weight ,
velocity, speed
e.t.c
QUALITATIVE DATA
Variable which we cannot
measure is Qualitative data.
Example:
Beauty, intelligence ,
happiness , satisfaction
e.t.c
DATA
Basic concepts of statistics

13. A characteristics of the individual of
the population which can varies
from person to person , objects to
objects and place to place is termed
as variable.
Basic concepts of statistics

14. Variable
DISCRETE VARIABLE
A variable which can count but
not measure is termed as
discrete variable.
Examples:
 No. of students in a school
 No. of products sold
 Name of days in a year
CONTINUOUS VARIABLE
A variable which cannot count
but measure is termed as
continuous variable.
Examples:
 Height of student in a school
 Weight of products
 Length of plot
Basic concepts of statistics

15. There are two main sources
Primary source of data Secondary source of data
RESEARCHER
DECISION MAKING

16. PRIMARY DATA SECONDARY DATA
• It is published or
unpublished data compiled
by some other agencies or
organization for some other
purposes
• It involves direct
investigation or first hand
data or afresh data obtained
by researcher.

17. PRIMARY SOURCE OF DATA COLLECTION
1) METHOD OF SAMPLE SURVEY
2) METHOD OF EXPERIMENTATION

18. • SAMPLING DESIGN
• MEASUREMENT SCALES
• QUESTIONNAIRE DESIGN
• QUESTIONNAIRE ADMINISTRATION
1) METHOD OF SAMPLE SURVEY

19. • LABORATORY EXPERIMENT
• FIELD EXPERIMENT
2) METHOD OF EXPERIMENTATION

20. Data editor
Output viewer
Syntax editor
Script window

21. • Data Editor
Spreadsheet-like system for defining, entering, editing,
and displaying data. Extension of the saved file will be
“sav.”

22. • Output Viewer
Displays output and errors. Extension of the saved file will
be “spv.”

23. • Syntax Editor
Text editor for syntax composition. Extension of the
saved file will be “sps.”

24. • Script Window
Provides the opportunity to write full-blown programs,
in a BASIC-like language. Text editor for syntax
composition. Extension of the saved file will be “sbs.”

25. • Rows are cases: Each row represents a case or an
observation. For example, each individual respondent
to a questionnaire is a case.
• Columns are variables: Each column represents a
variable or characteristic that is being measured. For
example, each item on a questionnaire is a variable.
• Cells contain values: Each cell contains a single value of
a variable for a case. The cell is where the case and the
variable intersect. Cells contain only data values. Unlike
spreadsheet programs, cells in the Data Editor cannot
contain formulas.

26. (cases)
C
O
L
U
M
N
S

30. Working is going
on…………………
thanks
There are three level of measurements