# D1 SPSS Intro 2020 21

```Escola de Medicina | Universidade do Minho
Biostatistics in Health Sciences
Introduction to IBM SPSS Statistics
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2020/21
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Introduction to IBM SPSS Statistics
IBM SPSS Statistics
 SPSS (Statistical Package for the Social Sciences) is a computer program used for statistical
analysis.
 was released in its first version in 1968 after being developed by Norman H. Nie and C.
Hadlai Hull. The original SPSS manual (Nie, Bent &amp; Hull, 1970) has been described as one of
&quot;sociology's most influential books&quot;.
 is among the most widely used programs for statistical analysis in social science. It is used
by market researchers, health researchers, survey companies, government, education
researchers, marketing organizations and others.
 Between 2009 and 2010 the premier software for SPSS was called PASW (Predictive
Analytics SoftWare) Statistics. The company announced July 28, 2009 that it was being
acquired by IBM for US\$1.2 billion. As of January 2010, it became &quot;SPSS: An IBM Company&quot;.
Wikipedia
Other packages: SAS, SysStat, Statistica, Stata ou os programas freeware R, PSPP, JASP e Jamovi.
Comparison of statistical packages: http://en.wikipedia.org/wiki/Comparison_of_statistical_packages
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Introduction to IBM SPSS Statistics
SPSS Tutorials
“Andy Field”), open the reproduction list SPSS Tutorials and watch the following
videos:
1 - Entering Data into SPSS
3 - Importing Data into SPSS from Excel
4 - Selecting Cases in SPSS
6 - Editing Graphs in SPSS
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Introduction to IBM SPSS Statistics
First screen
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Introduction to IBM SPSS Statistics
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Introduction to IBM SPSS Statistics
Role:
• Input: The variable will be used as an input (e.g., predictor, independent
variable).
• Target: The variable will be used as an output or target (e.g., dependent
variable).
• Both: The variable will be used as both input and output.
• None: The variable has no role assignment.
• Partition: The variable will be used to partition the data into separate
samples for training, testing, and validation.
• Split: Included for round-trip compatibility with IBM&reg; SPSS&reg; Modeler:
Variables with this role are not used as split-file variables in IBM&reg; SPSS&reg;
Statistics.
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Introduction to IBM SPSS Statistics
Scales of measurement - Stevens (1946, 1951)
 Nominal Data
 classification data, e.g. m/f
 no ordering, e.g. it makes no sense to state that M &gt; F; arbitrary labels, e.g., m/f, 0/1, etc
 Ordinal Data
 ordered but differences between values are not important
 e.g., Manchester Triage System (MTS) in a general emergency department; classifications of
burns; Likert scales, rank on a scale of 1..5 your degree of satisfaction
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Introduction to IBM SPSS Statistics
Scales of measurement - Stevens (1946, 1951)
 Interval Data
 ordered, constant scale, but no natural zero
 differences make sense, but ratios do not (e.g., 30&deg;-20&deg;=20&deg;-10&deg;, but 20&deg;/10&deg; is not twice as
hot!
 e.g., temperature (C,F), dates
 Ratio Data
 ordered, constant scale, natural zero
 e.g., height, weight, age, length
https://en.wikipedia.org/wiki/Level_of_measurement
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Introduction to IBM SPSS Statistics
Variable transformations
http://cmapspublic3.ihmc.us/rid=1074815492093_143863377_6575/Scales%20of%20Measurement.cmap
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Introduction to IBM SPSS Statistics
Variable transformations
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