Introduction to SPSS
Descriptive Statistics
Introduction to SPSS
 Statistics Program for the Social Sciences
(SPSS)
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
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Commonly used statistical software package
Very user-friendly
How you will be doing statistics in graduate
school
Introduction to SPSS
 Divided into “data view” & “variable view”
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

Default is data view
Data view – shows the data
Variable view – summary of variables,
options related to them
Switch between them by:
1.
2.
3.
clicking on tabs located on bottom left of screen
clicking on “View”  “Data/Variables” in top
menu
pressing CTRL+T
Entering Data
 Can either enter data by hand or import from
other programs (i.e. Excel)

Hand entering

Insert a variable by:
1. Right clicking one of the rows in variable view and
selecting “Insert Variable”
2. Entering a “Name” in variable view and pressing
“Enter” or “Tab”
3. Right clicking on a column in the data view and
selecting “Insert Variable”
4. Clicking on the “Insert Variable” icon in the Toolbar
5. Clicking on “Data”  “Insert Variable”
Entering Data

Define variables in variable view
 Name = Name of variable displayed in data view
 Type = Numeric, Comma, Dot, Scientific notation, Date,
Dollar, Custom currency, & String
 Width = # of digits displayed in data view
 Decimals = # of decimal places displayed in data view
 Label = Name of variable displayed when running
analyses
 Values = Value Labels – i.e. 1 = Male, 0 = Female
 Missing = Values that the system will recognize as missing
 Columns = # of columns used to display variable in data
view
 Align = variable left, right, or center aligned
 Measure = scale on which variable is measured –
Nominal, Ordinal, or Scale (Interval or Ratio)
Entering Data

Importing Data



Click “File”  “Open”  “Data”
Select the file type in question
If Excel:
1. Make sure top row of excel file lists variable names
& the variables all have different names
2. After selecting the file, click Enter – make sure the
box “Read variable names from the first row of
data” is clicked
3. Make sure you variable are defined properly in the
variable view
Menus
 File & Edit Menus
 Exactly the same as all Windows programs
 View Menu
 Allows you to customize the SPSS desktop
 Status Bar – “Processor Area” at the very bottom of
the screen
 Toolbars
 Fonts
 Grid Lines
 Value Labels – Make sure this is selected if you want
to use them
 Variables/Data view
Menus
 Data Menu
 Define Dates… = Inserts a Date variable
 Insert Variable
 Insert Case
 Go to Case…
 Sort Cases… = Ascending or descending order
 Transpose… = Switches cases and variables (former
in columns and latter in rows)
 Merge Files – More on this later
 Split Files – More on this later
 Select Cases = If condition is satisfied, Random
sample of cases, Based on time or case range, Use
filter variable
Splitting and Merging Files

Splitting
1.
2.
3.

Click on “Organize output by groups” – grouping variable should be
discrete (i.e. gender, hair color, etc.)
Click on grouping variable and move to “Groups Based on” box
Click “OK”
Merging


You can add either variables or cases
If adding variables:
1.
2.
3.
4.
5.
6.
7.
8.
9.
Make sure both files share at least one variable that is identical, the key
variable (i.e. SubID)
Make sure both files are sorted by this variable
Make sure, in both files, all cases have data for this variable and there are
no duplicate cases
Click on “Merge Files”  “Add Variables”
Find the file you wish to merge with the one you have open
The variable in the “Excluded Variables” box should be the key variable,
denoted by a (+) indicating its presence in both files
Click on “Match cases on key variables in sorted files”
Move the key variable to the “Key Variables” box
Click “OK”
Menus

Transform Menu

Compute...
1.
2.

Recode – Into Same/Different Variable
1.
2.
3.

Select variable(s) to recode and move to the “Variables” box
Click “Old and New Values”
Click “OK”
Count…
1.
2.
3.
4.

Name new variable in “Target Variable” box
Type equation in “Numeric Expression” box
Name new variable in “Target Variable” box
Select variable(s) with values to be counted & move to the “Numeric
Variables” box
Click “Define Values…”
Click “OK”
Rank Cases…
1.
2.
3.
Select variable(s) to rank and move to the “Variable(s)” box
Click “Assign Rank 1 to” either “Smallest value” or “Largest value”
Click “OK”
Obtaining Descriptive Statistics
 Click on “Analyze”  “Descriptive Statistics”

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Frequencies

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Use to determine counts on values of variables
Cut scores and %iles
Frequencies
EQ1
Statistics
Mean
Std. Error of Mean
Median
Mode
Std. Deviation
Variance
Skewness
Std. Error of Skewness
Kurtosis
Std. Error of Kurtosis
Range
Minimum
Maximum
Sum
Percentiles
Valid
Valid
Missing
25
33.33333333
50
66.66666667
75
614
17
4.26
.035
4.00
5
.864
.746
-1.497
.099
2.764
.197
4
1
5
2614
4.00
4.00
4.00
5.00
5.00
1
2
3
4
5
Total
System
Missing
Total
Percent
1.7
3.2
7.0
41.8
43.6
97.3
2.7
100.0
Valid Percent
1.8
3.3
7.2
43.0
44.8
100.0
Cumulative
Percent
1.8
5.0
12.2
55.2
100.0
EQ1
300
200
100
Frequency
EQ1
N
Frequency
11
20
44
264
275
614
17
631
Std. Dev = .86
Mean = 4.3
N = 614.00
0
1.0
EQ1
2.0
3.0
4.0
5.0
Descriptives
 Click on “Analyze”  “Descriptive Statistics” 
 Descriptives
 Use to get descriptive statistics (central tendency,
variability, etc.)
 Use to convert variables to z-scores
Descriptive Statistics
EQ1
Valid N (listwise)
N
Statistic
614
614
Range
Statistic
4
Minimum
Statistic
1
Maximum
Statistic
5
Sum
Statistic
2614
Mean
Statistic
Std. Error
4.26
.03
Std.
Deviation
Statistic
.864
Variance
Statistic
.746
Kurtosis
Statistic
Std. Error
2.764
.197
Explore
 Click on “Analyze”  “Descriptive Statistics”


Explore

Use to examine descriptive statistics by grouping
variable
Explore
Descriptives
EQ1
GENDER
Female
Case Processing Summary
Valid
EQ1
GENDER
Female
Male
N
326
286
Percent
96.2%
98.6%
Cases
Missing
N
Percent
13
3.8%
4
1.4%
Total
N
339
290
Percent
100.0%
100.0%
Male
Mean
95% Confidence
Interval for Mean
5% Trimmed Mean
Median
Variance
Std. Deviation
Minimum
Maximum
Range
Interquartile Rang e
Skewness
Kurtosis
Mean
95% Confidence
Interval for Mean
5% Trimmed Mean
Median
Variance
Std. Deviation
Minimum
Maximum
Range
Interquartile Rang e
Skewness
Kurtosis
Lower Bound
Upper Bound
Lower Bound
Upper Bound
Statistic
4.30
4.21
Std. Error
.043
4.38
4.37
4.00
.591
.769
1
5
4
1.00
-1.261
2.251
4.21
4.10
.135
.269
.057
4.33
4.33
4.00
.926
.962
1
5
4
1.00
-1.556
2.479
.144
.287
Explore
Percentiles
Weighted
Average(Definition 1)
EQ1
Tukey's Hinges
EQ1
GENDER
Female
Male
Female
Male
5
10
3.00
3.00
3.00
2.00
25
4.00
4.00
4.00
4.00
Percentiles
50
4.00
4.00
4.00
4.00
75
5.00
5.00
5.00
5.00
90
5.00
5.00
95
5.00
5.00
Extreme Values
EQ1
GENDER
Female
Highest
Lowest
Tests of Normality
a
EQ1
GENDER
Female
Male
Kolmog orov-Smirnov
Statistic
df
Sig .
.261
326
.000
.269
286
.000
Statistic
.757
.742
Shapiro-Wilk
df
326
286
Sig .
.000
.000
Male
Highest
a. Lilliefors Significance Correction
Lowest
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
Case Number
339
182
242
121
145
150
184
3
258
113
421
522
463
551
494
600
355
566
377
525
a. Only a partial list of cases with the value 5 are shown in the
table of upper extremes.
b. Only a partial list of cases with the value 2 are shown in the
table of lower extremes.
c. Only a partial list of cases with the value 1 are shown in the
table of lower extremes.
Value
5
5
5
5
.a
1
1
2
2
.b
5
5
5
5
.a
1
1
1
1
.c
Explore
Histogram
Histogram
For GENDER= Male
For GENDER= Female
140
160
140
120
120
100
100
80
80
60
Std. Dev = .77
20
Mean = 4.3
0
N = 326.00
1.0
2.0
3.0
4.0
40
Frequency
40
Std. Dev = .96
20
Mean = 4.2
N = 286.00
0
1.0
5.0
EQ1
EQ1
6
5
4
3
EQ1
Frequency
60
2
3
258
113
28
27
238
191
260
254
349
381
408
378
546
538
404
415
593
390
597
1
150
184
600
355
566
377
525
503
520
576
409
0
N=
GENDER
326
286
Female
Male
2.0
3.0
4.0
5.0