Introduction of spss

1. SPSS (Statistical Package for Social Science)
Dr.LILLY GEORGE
Head of the Department,
Department of Statistics,
St. Joseph’s College,
Trichy.

2. Introduction: What is SPSS?
 Originally it is an acronym of Statistical Package for
the Social Science but now it stands for Statistical
Product and Service Solutions
 One of the most popular statistical packages which
can perform highly complex data manipulation and
analysis with simple instructions

3. The default window will have the data editor
There are two sheets in the window:
1. Data view 2. Variable view
Opening SPSS

4. Scales of Measurement
•Nominal Scale - groups or classes
Gender
•Ordinal Scale - order matters
Ranks (top ten videos)
•Interval Scale - difference or distance matters – has
arbitrary zero value.
Temperatures (0F, 0C), Likert Scale
•Ratio Scale - Ratio matters – has a natural zero value.
Salaries

5. Frequencies
This analysis produces frequency tables showing
frequency counts and percentages of the values of
individual variables.
Descriptives
This analysis shows the maximum, minimum,
mean, and standard deviation of the variables
Linear regression analysis
Linear Regression estimates the coefficients of
the linear equation
The basic analysis of SPSS that will be introduced
in this class

6. Frequencies
Click ‘Analyze,’ ‘Descriptive statistics,’ then
click ‘Frequencies’

8. Descriptives
The options allows you to analyze other
descriptive statistics besides the mean and Std.
Click ‘variance’ and ‘kurtosis’
Finally click ‘Continue’
Click
Click

9. Descriptives
Finally Click OK in the Descriptives box. You
will be able to see the result of the analysis.

10. Click ‘Graphs,’ ‘Legacy Dialogs,’ ‘Interactive,’ and
‘Scatter plot’ from the main menu.
Graphs

12. Bar Chart
GENDER
Male
Female
Missing
Mean
EQ1
4.4
4.3
4.2
4.1
4.0
3.9
GENDER
Male
Female
Missing
Percent
60
50
40
30
20
10
0

13. Pie Chart
Male
Female
Missing
EQ5
EQ4
EQ3
EQ2
EQ1

14. Line Chart
GENDER
Male
Female
Missing
Percent
60
50
40
30
20
10
0
GENDER
Male
Female
Missing
Mean
EQ1
4.4
4.3
4.2
4.1
4.0
3.9

15. Histogram
Histogram
Really just a bar chart that displays “Num of Cases” only
Click “Display Normal Curve” to inspect if your distribution
deviates from normal
EQ1
5.0
4.0
3.0
2.0
1.0
300
200
100
0
Std. Dev = .86
Mean = 4.3
N = 614.00

16. Regression Analysis
Click ‘Analyze,’ ‘Regression,’ then
click ‘Linear’ from the main menu.

17. Regression Analysis

18. One-Sample t Test
Tests for difference between sample mean and pre-determined
population mean
Click “Analyze”  “Compare Means”  “One- Sample T
Test…”
“Test Value” = Predetermined population mean
Options:
Exclude Cases Listwise = If multiple variables used, only use
cases that have values on ALL variables
Exclude Cases Analysis by Analysis

19. One-Sample T Test
One-Sample Statistics
613 2.83 1.026 .041
EQ2
N Mean Std. Deviation
Std. Error
Mean
One-Sample Test
68.368 612 .000 2.83 2.75 2.91
EQ2
t df Sig. (2-tailed)
Mean
Difference Lower Upper
95% Confidence
Interval of the
Difference
Test Value = 0

20. Independent-Samples t Test
Tests if two unrelated samples differ significantly from one another
Click “Analyze”  “Compare Means”  “Independent-Samples T
Test…”
“Test Variable(s)” = DV
“Grouping Variable” = IV
Click “Define Groups…”
MergeFile1.sav – Male = 1; Female = 0
If IV dimensional, can use cut point to create groups – i.e. x > 7 =
Grp 1, x ≤ 7 = Grp 2
Levene’s Test for Equality of Variances
If significant, equal variances cannot be assumed

21. Independent-Samples t Test
Group Statistics
326 4.30 .769 .043
286 4.21 .962 .057
GENDER
Female
Male
EQ1
N Mean Std. Deviation
Std. Error
Mean
Independent Samples Test
5.118 .024 1.203 610 .230 .08 .070 -.053 .222
1.185 543.961 .236 .08 .071 -.055 .224
Equal variances
assumed
Equal variances
not assumed
EQ1
F Sig.
Levene's Test for
Equality of Variances
t df Sig. (2-tailed)
Mean
Difference
Std. Error
Difference Lower Upper
95% Confidence
Interval of the
Difference
t-test for Equality of Means

22. Paired-Samples t Test
Tests if two related samples differ significantly from one another
Click “Analyze”  “Compare Means”  “Paired-Samples T Test…”
Paired Samples Statistics
4.26 613 .860 .035
2.83 613 1.026 .041
EQ1
EQ2
Pair
1
Mean N Std. Deviation
Std. Error
Mean
Paired Samples Correlations
613 .016 .684
EQ1 & EQ2
Pair 1
N Correlation Sig.
PairedSamples Test
1.43 1.327 .054 1.32 1.53 26.657 612 .000
EQ1 - EQ2
Pair 1
Mean Std. Deviation
Std. Error
Mean Lower Upper
95% Confidence
Interval of the
Difference
Paired Differences
t df Sig. (2-tailed)

23. THANK YOU