SPSS is a widely used statistical software package for analyzing social science and medical data. It allows users to easily enter, clean, transform, and analyze data through a graphical user interface with drop-down menus rather than commands. Data is organized in SPSS with variables and cases, and can be imported from Excel or directly entered. Common tasks include sorting, merging, and recoding data to prepare it for statistical analysis.

1. Presented by:
SUBODH KHANAL
Asst. Professor
Paklihawa Campus
Institute of Agriculture and Animal Science

2. S PS S
Statistical Package for the Social Sciences

3. SPSS is
 Asoftware package (program) used for statistical analysis.
 Long produced by SPSS Inc., (Incorporation )it was acquired by IBM in 2009
($ 1.2 billion in cash). The
SPSS Statistics.
current versions are officially named IBM
 widely used for statistical analysis in social science, market researchers, health
researchers,
data miners
survey companies, government, education researchers, marketing,

4. Why SPSS???
 Popular and has been used extensively in medical and biological
researches.
 More user-friendly (data analysis presentation) than other
statistical software (e.g., S-Plus, R, SAS) (Drop down menus not
commands!).
 Contain all statistical procedures which the researcher is in need

5. 5
SPSS Windows has 3 windows:
Data Editor
Syntax Editor, which displays syntax files
Output: Viewer or Draft Viewer which displays the output files
The Data Editor has two parts:
Data View window, which displays data from the active file in spreadsheet format
Variable View window, which displays metadata or information about the data in the active file, such as
variable names and labels, value labels, formats, and missing value indicators.

6. Data analysis

7. Data editor has two “views”
 Data View Shows actual data values
 Variable View
variables.
Shows variable information for all
 Two tabs at on the bottom of the left hand side switching between
them.

8. Variables
Cases

9. 9
SPSS Data View

10. 10
SPSS Variable View

11. 3 Variables
Breed
Milk yield
Udder size
1stCase 1= cow
under study
No. of cases = no. of
experimental units e.g.
individuals -animals

13. Variable View
create variable names and define the attributes of each variable.
Name name for each variable.
 only of letters, and the underbar (_)
 No pure numbers - space - dot .
Type
Width
Decimals
Label
specify type the variable. string
space the entries in the Data
or numeric type.
View will be for this variable.
decimal places will be shown for this variable in the Data View.
give a variable a label or title. makes all output much more readable.

14. Values specify numerical values for each category of categorical variable.
For example for the variable SEX 1 for Male, 2 for Females .
Missing specify values for a variable indicate missing data.
Columns spaces will be allocated for the variable in the Data View. different
from width in that width limits the number of spaces for the actual number.
Columns limits how many spaces will be visible in the Data View.
Align either left aligns, centers, or right aligns the entries for the variable.

15. Measure
Ascale variable
type of variable.
is a quantitative variable.
categorical variable where the categories have aAn ordinal variable
natural order such as
Anominal variable
poor, fair, good, better, best.
categorical variable no natural order to the categories,
such as male, female.

16. Entering and Saving Data

17. method
SPSS
SPSS Importing function
Cut and paste
Data entry
Directly into SPSS
.sav file
Excel spreadsheet
(.xls, .xlsx)

18. 18
Figure 1. Data from Hell

19. 19
Data from Heaven

20.  7.4.4 Example
 Consider the comparison of the mean body weights at the time of mating in one
group of ewes which have been flushed (put on a high plane of nutrition for 2–3
weeks prior to mating) and another group which have not. Each ewe in a random
sample of 54 ewes is randomly allocated to the flushed or control group. Table
7.2 shows the weights of two samples of 24 flushed and 30 control ewes.

22.  How many variables in this data set ?

23.  2 Variables:
 Ewe Weight (Quantitative)
 Group (Qualitative): 0;Flushed, 1;control

24. IMPORTING DATA INTO SPSS
• Direct data entry in SPSS making a template
• Data import from excel or any other kind of file

25. Direct data entry in SPSS

30. 30
Importing data from Excel spreadsheet into SPSS.
In SPSS, go to:
File, Open, Data
Select Type of file (for example, Excel) you want to open
Select File name you want to open

31. DATA CLEANING
• Check for data entry and coding errors
• Wild code checking ( codes beyond the specified codes)
• Consistency checking

33. After DATA CLEANING……
• SORT function
• MERGE function
• RECODE

34. SORT FUNCTION

35. SELECT function

36. MERGE function

38. 38
Data merging in SPSS (1)
1. Make sure that both files are sorted by Key variable in ascending order

39. 39
Data merging in SPSS (2)
4. Select the dataset you want to merge into the working file.

40. 40
Data merging in SPSS (3)
5. Click on Match cases on key variables in sorted files,
6. Click on Both files provide cases
7. Highlight ID in the excluded variables box, then click ► near key Variables

41. Data transformation

44. e.g. Bramins vs rest
janajati vs rest