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
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
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
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