Data Analysis Using SAS
Autor Chao-Ying Joanne Pengen Limba Engleză Electronic book text – 8 aug 2012
Data Analysis Using SASis a complete resource for Data Analysis I and II, Statistics I and II, Quantitative Reasoning, and SAS Programming courses across the social and behavioral sciences and health - especially those that carry a lab component.
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Specificații
ISBN-13: 9781452211862
ISBN-10: 1452211868
Pagini: 640
Dimensiuni: 178 x 254 mm
Ediția:1
Editura: SAGE Publications
Colecția Sage Publications, Inc
Locul publicării:Thousand Oaks, United States
ISBN-10: 1452211868
Pagini: 640
Dimensiuni: 178 x 254 mm
Ediția:1
Editura: SAGE Publications
Colecția Sage Publications, Inc
Locul publicării:Thousand Oaks, United States
Recenzii
“Peng
provides
an
excellent
overview
of
data
analysis
using
the
powerful
statistical
software
package
SAS.
This
book
is
quite
appropriate
as
a
self-placed
tutorial
for
researchers,
as
well
as
a
textbook
or
supplemental
workbook
for
data
analysis
courses
such
as
statistics
or
research
methods.
Peng
provides
detailed
coverage
of
SAS
capabilities
using
step-by-step
procedures
and
includes
numerous
comprehensive
graphics
and
figures,
as
well
as
SAS
printouts.
Readers
do
not
need
a
background
in
computer
science
or
programming.
Includes
numerous
examples
in
education,
health
sciences,
and
business.”
Cuprins
PART
I.
INTRODUCTION
TO
SAS
AND
BASIC
DATA
ANALYSIS
1. Why do you need to learn SAS for data analyses?
2. Where do you start?
3. How to prepare data for SAS processing
4. From data to a SAS data set
5. Enhancing SAS programs and output
6. Verifying data
7. Data transformation
PART II. STATISTICAL PROCEDURES
8. Quick descriptive analysis
9. Comprehensive descriptive analysis and normality test
10.Graphing data
11. Categorical data analysis
12. T-test of population means
13. Analysis of variance
14. Inferences about two or more population typical scores by ranks
15. Examining trends in data
16. Correlation
17. When do you stop worrying and start loving regression?
PART III. ADVANCED DATA AND FILE MANAGEMENT
18. Selecting variables or observations from a SAS data set
19. Repetitive and conditional data processing
20. Structuring SAS data sets
Appendix A. What lies beyond this book? Information on reference books, hotlines, and Internet resources
Appendix B. Data sets used in this book
Appendix C. Converting SPSS, STATA, Excel, Minitab, Systat data set files to SAS data sets or data set files
1. Why do you need to learn SAS for data analyses?
2. Where do you start?
3. How to prepare data for SAS processing
4. From data to a SAS data set
5. Enhancing SAS programs and output
6. Verifying data
7. Data transformation
PART II. STATISTICAL PROCEDURES
8. Quick descriptive analysis
9. Comprehensive descriptive analysis and normality test
10.Graphing data
11. Categorical data analysis
12. T-test of population means
13. Analysis of variance
14. Inferences about two or more population typical scores by ranks
15. Examining trends in data
16. Correlation
17. When do you stop worrying and start loving regression?
PART III. ADVANCED DATA AND FILE MANAGEMENT
18. Selecting variables or observations from a SAS data set
19. Repetitive and conditional data processing
20. Structuring SAS data sets
Appendix A. What lies beyond this book? Information on reference books, hotlines, and Internet resources
Appendix B. Data sets used in this book
Appendix C. Converting SPSS, STATA, Excel, Minitab, Systat data set files to SAS data sets or data set files
Descriere
This
book
provides
students
with
a
hands-on,
exercise-heavy
method
for
learning
basic
to
intermediate
SAS
commands
while
understanding
how
to
apply
statistics
and
reasoning
to
real-world
problems.