Intermediate statistics: a modern approach ; [SAS, SPSS]
Gespeichert in:
1. Verfasser: | |
---|---|
Format: | Buch |
Sprache: | English |
Veröffentlicht: |
New York [u.a.]
Erlbaum
2007
|
Ausgabe: | 3. ed. |
Schlagworte: | |
Online-Zugang: | Publisher description Inhaltsverzeichnis |
Beschreibung: | Nebentitel: SAS intermediate statistics |
Beschreibung: | XII, 460 S. Ill., graph. Darst. 24 cm CD-ROM (12 cm) |
ISBN: | 9780805854657 0805854657 0805854665 9780805854664 |
Internformat
MARC
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100 | 1 | |a Stevens, James P. |e Verfasser |4 aut | |
245 | 1 | 0 | |a Intermediate statistics |b a modern approach ; [SAS, SPSS] |c James P. Stevens |
250 | |a 3. ed. | ||
264 | 1 | |a New York [u.a.] |b Erlbaum |c 2007 | |
300 | |a XII, 460 S. |b Ill., graph. Darst. |c 24 cm |e CD-ROM (12 cm) | ||
336 | |b txt |2 rdacontent | ||
337 | |b n |2 rdamedia | ||
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Datensatz im Suchindex
_version_ | 1804136585502916608 |
---|---|
adam_text | Contents
Preface
xi
Chapter
1
INTRODUCTION
1
1.1
Focus and Overview of Topics
1.2
Some Basic Descriptive Statistics
1.3
Summation Notation
1.4
t
Test for Independent Samples
1.5
t
Test for Dependent Samples
1.6
Outliers
1.7
SPSS and
SAS
Statistical Packages
1.8
SPSS for Windows—Release
12.0
1.9
Data Files
1.10
Data Entry
1.11
Editing
a
Dataset
1.12
Splitting and Merging Files
1.13
Two Ways of Running Analyses on SPSS
1.14
SPSS Output Navigator
1.15
SAS
and SPSS Output for Correlations,
Descriptives,
and
t
Tests
1.16
Data Sets on Compact Disk
Appendix Obtaining the Mean and Variance on the
ТІ-ЗОХа
Calculator
ONE WAY ANALYSIS OF VARIANCE
45
2.1
Introduction
2.2
Rationale for ANOVA
2.3
Numerical Example
2.4
Expected Mean Squares
2.5
MSW and MSb as Variances
VÍ
CONTENTS
2.6
A Linear
Model for the Data
2.7
Assumptions in ANOVA
2.8
The Independence Assumption
2.9
ANOVA on SPSS and
SAS
2.10
Post Hoc Procedures
2.11
Tukey Procedure
2.12
The
Scheffé
Procedure
2.13
Heterogeneous Variances and Unequal Group Sizes
2.14
Measures of Association (Variance Accounted For)
2.15
Planned Comparisons
2.16
Test Statistic for Planned Comparisons
2.17
Planned Comparisons on SPSS and
SAS
2.18
The Effect of an Outlier on an ANOVA
2.19
Multivariate Analysis of Variance
2.20
Summary
Appendix
Chapter
3
POWER ANALYSIS
105
3.1
Introduction
3.2
t
Test for Independent Samples
3.3
A Priori and Post Hoc Estimation of Power
3.4
Estimation of Power for One Way Analysis of Variance
3.5
A Priori Estimation of Subjects Needed for a Given Power
3.6
Ways of Improving Power
3.7
Power Estimation on SPSS
MÁNOVA
3.8
Summary
Chapter
4
FACTORIAL ANALYSIS OF VARIANCE
123
4.1
Introduction
4.2
Numerical Calculations for Two Way ANOVA
4.3
Balanced and Unbalanced Designs
4.4
Higher Order Designs
4.5
A Comprehensive Computer Example Using Real Data
4.6
Power Analysis
4.7
Fixed and Random Factors
4.8
Summary
Appendix Doing a Balanced Two Way ANOVA With a Calculator
CONTENTS
VII
Chapter
5
REPEATED MEASURES ANALYSIS
181
5.1
Introduction
5.2
Advantages and Disadvantages of Repeated Measures Designs
5.3
Single Group Repeated Measures
5.4
Completely Randomized Design
5.5
Univariate Repeated Measures Analysis
5.6
Assumptions in Repeated Measures Analysis
5.7
Should We Use the Univariate or Multivariate Approach?
5.8
Computer Analysis on
SAS
and SPSS for Example
5.9
Post Hoc Procedures in Repeated Measures Analysis
5.10
One Between and One Within Factor
—
A Trend Analysis
5.11
Post Hoc Procedures for the One Between and One Within Design
5.12
One Between and Two Within Factors
5.13
Totally Within Designs
5.14
Planned Comparisons in Repeated Measures Designs
5.15
Summary
Chapter
6
SIMPLE AND MULTIPLE REGRESSION
219
6.1
Simple Regression
6.2
Assumptions for the Errors
6.3
Influential Data Points
6.4
Multiple Regression
6.5
Breakdown of Sum of Squares in Regression and
F
Test for Multiple Correlation
6.6
Relationship of Simple Correlations to Multiple Correlation
6.7
Multicollinearity
6.8
Model Selection
6.9
Two Computer Examples
6.10
Checking Assumptions for the Regression Model
6.11
Model Validation
6.12
Importance of the Order of Predictors in Regression Analysis
6.13
Other Important Issues
6.14
Outliers and Influential Data Points
6.15
Further Discussion of the Two Computer Examples
6.16
Sample Size Determination for a Reliable Prediction Equation
6.17
ANOVA as a Special Case of Regression Analysis
6.18
Summary of Important Points
Appendix The PRESS Statistic
VIU
CONTENTS
Chapter
7
ANALYSIS OF COVARIANCE
285
7.1
Introduction
7.2
Purposes of Covariance
7.3
Adjustment of
Posttest
Means
7.4
Reduction of Error Variance
7.5
Choice of Covariates
7.6
Numerical Example
7.7
Assumptions in Analysis of Covariance
7.8
Use of ANCOVA with Intact Groups
7.9
Computer Example for ANCOVA
7.10
Alternative Analyses
7.11
An Alternative to the Johnson-Neyman Technique
7.12
Use of Several Covariates
7.13
Computer Example with Two Covariates
7.14
Summary
Chapter
8
HIERARCHICAL LINEAR MODELING
321
8.1
Introduction
8.2
Problems Using Single-Level Analyses of Multilevel Data
8.3
Formulation of the Multilevel Model
8.4
Two-Level Model
—
General Formulation
8.5
HLM6 Software
8.6
Two Level Example
—
Student and Classroom Data
8.7
HLM Software Output
8.8
Adding Level One Predictors to the HLM
8.9
Addition of a Level Two Predictor to a Two Level HLM
8.10
Evaluating the Efficacy of a Treatment
8.11
Final Comments on Him
Appendix A
DATA SETS
365
A.1 Clinical Data
A.2 Alcoholics Data
A.3 Sesame Street Data
A.4 Headache Data
A.5 Cartoon Data
CONTENTS
IX
A.6
Attitude Data
A.7 National
Academy of
Sciences Data
Α.
8
Agresti
Home Sales Data
Appendix
В
STATISTICAL TABLES
Table
В
. 1
Critical Values for
F
Table B.2 Percentile Points of Studentized Range Statistic
Table B.3 Critical Values for Dunnett s Test
Table B.4 Critical Values for
F
(max) Statistic
Table B.5 Critical Values for Bryant-Paulson Procedure
Appendix
С
POWER TABLES
Table
С
1
Power of
F
Test at
α
= .05,
и
= 1
Table C.2 Power of
F
Test at
α
= .05,
и =
2
Table C.3 Power of
F
Test at
α
= .05,
и =
3
Table C.4 Power of
F
Test at
α
= .05,
и
= 4
Table C.5 Power of
F
Test at a
= . 10,
и
= 1
Table C.6 Power of
F
Test at
α
= .10,
и
= 2
Table C.7 Power of
F
Testata
=.10,
и = 3
Table C.8 Power of
F
Test at
α
= .10,
и
= 4
399
413
References
Answers to Selected Exercises
Author Index
Subject Index
423
431
453
457
|
adam_txt |
Contents
Preface
xi
Chapter
1
INTRODUCTION
1
1.1
Focus and Overview of Topics
1.2
Some Basic Descriptive Statistics
1.3
Summation Notation
1.4
t
Test for Independent Samples
1.5
t
Test for Dependent Samples
1.6
Outliers
1.7
SPSS and
SAS
Statistical Packages
1.8
SPSS for Windows—Release
12.0
1.9
Data Files
1.10
Data Entry
1.11
Editing
a
Dataset
1.12
Splitting and Merging Files
1.13
Two Ways of Running Analyses on SPSS
1.14
SPSS Output Navigator
1.15
SAS
and SPSS Output for Correlations,
Descriptives,
and
t
Tests
1.16
Data Sets on Compact Disk
Appendix Obtaining the Mean and Variance on the
ТІ-ЗОХа
Calculator
ONE WAY ANALYSIS OF VARIANCE
45
2.1
Introduction
2.2
Rationale for ANOVA
2.3
Numerical Example
2.4
Expected Mean Squares
2.5
MSW and MSb as Variances
VÍ
CONTENTS
2.6
A Linear
Model for the Data
2.7
Assumptions in ANOVA
2.8
The Independence Assumption
2.9
ANOVA on SPSS and
SAS
2.10
Post Hoc Procedures
2.11
Tukey Procedure
2.12
The
Scheffé
Procedure
2.13
Heterogeneous Variances and Unequal Group Sizes
2.14
Measures of Association (Variance Accounted For)
2.15
Planned Comparisons
2.16
Test Statistic for Planned Comparisons
2.17
Planned Comparisons on SPSS and
SAS
2.18
The Effect of an Outlier on an ANOVA
2.19
Multivariate Analysis of Variance
2.20
Summary
Appendix
Chapter
3
POWER ANALYSIS
105
3.1
Introduction
3.2
t
Test for Independent Samples
3.3
A Priori and Post Hoc Estimation of Power
3.4
Estimation of Power for One Way Analysis of Variance
3.5
A Priori Estimation of Subjects Needed for a Given Power
3.6
Ways of Improving Power
3.7
Power Estimation on SPSS
MÁNOVA
3.8
Summary
Chapter
4
FACTORIAL ANALYSIS OF VARIANCE
123
4.1
Introduction
4.2
Numerical Calculations for Two Way ANOVA
4.3
Balanced and Unbalanced Designs
4.4
Higher Order Designs
4.5
A Comprehensive Computer Example Using Real Data
4.6
Power Analysis
4.7
Fixed and Random Factors
4.8
Summary
Appendix Doing a Balanced Two Way ANOVA With a Calculator
CONTENTS
VII
Chapter
5
REPEATED MEASURES ANALYSIS
181
5.1
Introduction
5.2
Advantages and Disadvantages of Repeated Measures Designs
5.3
Single Group Repeated Measures
5.4
Completely Randomized Design
5.5
Univariate Repeated Measures Analysis
5.6
Assumptions in Repeated Measures Analysis
5.7
Should We Use the Univariate or Multivariate Approach?
5.8
Computer Analysis on
SAS
and SPSS for Example
5.9
Post Hoc Procedures in Repeated Measures Analysis
5.10
One Between and One Within Factor
—
A Trend Analysis
5.11
Post Hoc Procedures for the One Between and One Within Design
5.12
One Between and Two Within Factors
5.13
Totally Within Designs
5.14
Planned Comparisons in Repeated Measures Designs
5.15
Summary
Chapter
6
SIMPLE AND MULTIPLE REGRESSION
219
6.1
Simple Regression
6.2
Assumptions for the Errors
6.3
Influential Data Points
6.4
Multiple Regression
6.5
Breakdown of Sum of Squares in Regression and
F
Test for Multiple Correlation
6.6
Relationship of Simple Correlations to Multiple Correlation
6.7
Multicollinearity
6.8
Model Selection
6.9
Two Computer Examples
6.10
Checking Assumptions for the Regression Model
6.11
Model Validation
6.12
Importance of the Order of Predictors in Regression Analysis
6.13
Other Important Issues
6.14
Outliers and Influential Data Points
6.15
Further Discussion of the Two Computer Examples
6.16
Sample Size Determination for a Reliable Prediction Equation
6.17
ANOVA as a Special Case of Regression Analysis
6.18
Summary of Important Points
Appendix The PRESS Statistic
VIU
CONTENTS
Chapter
7
ANALYSIS OF COVARIANCE
285
7.1
Introduction
7.2
Purposes of Covariance
7.3
Adjustment of
Posttest
Means
7.4
Reduction of Error Variance
7.5
Choice of Covariates
7.6
Numerical Example
7.7
Assumptions in Analysis of Covariance
7.8
Use of ANCOVA with Intact Groups
7.9
Computer Example for ANCOVA
7.10
Alternative Analyses
7.11
An Alternative to the Johnson-Neyman Technique
7.12
Use of Several Covariates
7.13
Computer Example with Two Covariates
7.14
Summary
Chapter
8
HIERARCHICAL LINEAR MODELING
321
8.1
Introduction
8.2
Problems Using Single-Level Analyses of Multilevel Data
8.3
Formulation of the Multilevel Model
8.4
Two-Level Model
—
General Formulation
8.5
HLM6 Software
8.6
Two Level Example
—
Student and Classroom Data
8.7
HLM Software Output
8.8
Adding Level One Predictors to the HLM
8.9
Addition of a Level Two Predictor to a Two Level HLM
8.10
Evaluating the Efficacy of a Treatment
8.11
Final Comments on Him
Appendix A
DATA SETS
365
A.1 Clinical Data
A.2 Alcoholics Data
A.3 Sesame Street Data
A.4 Headache Data
A.5 Cartoon Data
CONTENTS
IX
A.6
Attitude Data
A.7 National
Academy of
Sciences Data
Α.
8
Agresti
Home Sales Data
Appendix
В
STATISTICAL TABLES
Table
В
. 1
Critical Values for
F
Table B.2 Percentile Points of Studentized Range Statistic
Table B.3 Critical Values for Dunnett's Test
Table B.4 Critical Values for
F
(max) Statistic
Table B.5 Critical Values for Bryant-Paulson Procedure
Appendix
С
POWER TABLES
Table
С
1
Power of
F
Test at
α
= .05,
и
= 1
Table C.2 Power of
F
Test at
α
= .05,
и =
2
Table C.3 Power of
F
Test at
α
= .05,
и =
3
Table C.4 Power of
F
Test at
α
= .05,
и
= 4
Table C.5 Power of
F
Test at a
= . 10,
и
= 1
Table C.6 Power of
F
Test at
α
= .10,
и
= 2
Table C.7 Power of
F
Testata
=.10,
и = 3
Table C.8 Power of
F
Test at
α
= .10,
и
= 4
399
413
References
Answers to Selected Exercises
Author Index
Subject Index
423
431
453
457 |
any_adam_object | 1 |
any_adam_object_boolean | 1 |
author | Stevens, James P. |
author_facet | Stevens, James P. |
author_role | aut |
author_sort | Stevens, James P. |
author_variant | j p s jp jps |
building | Verbundindex |
bvnumber | BV022490549 |
callnumber-first | Q - Science |
callnumber-label | QA276 |
callnumber-raw | QA276 |
callnumber-search | QA276 |
callnumber-sort | QA 3276 |
callnumber-subject | QA - Mathematics |
classification_rvk | SK 830 SK 840 QH 231 CM 4000 |
ctrlnum | (OCoLC)255863177 (DE-599)BVBBV022490549 |
dewey-full | 519.5 |
dewey-hundreds | 500 - Natural sciences and mathematics |
dewey-ones | 519 - Probabilities and applied mathematics |
dewey-raw | 519.5 |
dewey-search | 519.5 |
dewey-sort | 3519.5 |
dewey-tens | 510 - Mathematics |
discipline | Psychologie Mathematik Wirtschaftswissenschaften |
discipline_str_mv | Psychologie Mathematik Wirtschaftswissenschaften |
edition | 3. ed. |
format | Book |
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id | DE-604.BV022490549 |
illustrated | Illustrated |
index_date | 2024-07-02T17:51:44Z |
indexdate | 2024-07-09T20:58:44Z |
institution | BVB |
isbn | 9780805854657 0805854657 0805854665 9780805854664 |
language | English |
lccn | 99032699 |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-015697768 |
oclc_num | 255863177 |
open_access_boolean | |
owner | DE-824 DE-355 DE-BY-UBR DE-11 DE-188 |
owner_facet | DE-824 DE-355 DE-BY-UBR DE-11 DE-188 |
physical | XII, 460 S. Ill., graph. Darst. 24 cm CD-ROM (12 cm) |
publishDate | 2007 |
publishDateSearch | 2007 |
publishDateSort | 2007 |
publisher | Erlbaum |
record_format | marc |
spelling | Stevens, James P. Verfasser aut Intermediate statistics a modern approach ; [SAS, SPSS] James P. Stevens 3. ed. New York [u.a.] Erlbaum 2007 XII, 460 S. Ill., graph. Darst. 24 cm CD-ROM (12 cm) txt rdacontent n rdamedia nc rdacarrier Nebentitel: SAS intermediate statistics Statistik Statistics Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd rswk-swf Statistik (DE-588)4056995-0 gnd rswk-swf Sozialwissenschaften (DE-588)4055916-6 gnd rswk-swf Anwendung (DE-588)4196864-5 gnd rswk-swf Multivariate Analyse (DE-588)4040708-1 gnd rswk-swf Entscheidungstheorie (DE-588)4138606-1 gnd rswk-swf Bayes-Entscheidungstheorie (DE-588)4144220-9 s Statistik (DE-588)4056995-0 s DE-604 Anwendung (DE-588)4196864-5 s Entscheidungstheorie (DE-588)4138606-1 s Multivariate Analyse (DE-588)4040708-1 s Sozialwissenschaften (DE-588)4055916-6 s http://www.loc.gov/catdir/enhancements/fy0709/99032699-d.html Publisher description Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015697768&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | Stevens, James P. Intermediate statistics a modern approach ; [SAS, SPSS] Statistik Statistics Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd Statistik (DE-588)4056995-0 gnd Sozialwissenschaften (DE-588)4055916-6 gnd Anwendung (DE-588)4196864-5 gnd Multivariate Analyse (DE-588)4040708-1 gnd Entscheidungstheorie (DE-588)4138606-1 gnd |
subject_GND | (DE-588)4144220-9 (DE-588)4056995-0 (DE-588)4055916-6 (DE-588)4196864-5 (DE-588)4040708-1 (DE-588)4138606-1 |
title | Intermediate statistics a modern approach ; [SAS, SPSS] |
title_auth | Intermediate statistics a modern approach ; [SAS, SPSS] |
title_exact_search | Intermediate statistics a modern approach ; [SAS, SPSS] |
title_exact_search_txtP | Intermediate statistics a modern approach ; [SAS, SPSS] |
title_full | Intermediate statistics a modern approach ; [SAS, SPSS] James P. Stevens |
title_fullStr | Intermediate statistics a modern approach ; [SAS, SPSS] James P. Stevens |
title_full_unstemmed | Intermediate statistics a modern approach ; [SAS, SPSS] James P. Stevens |
title_short | Intermediate statistics |
title_sort | intermediate statistics a modern approach sas spss |
title_sub | a modern approach ; [SAS, SPSS] |
topic | Statistik Statistics Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd Statistik (DE-588)4056995-0 gnd Sozialwissenschaften (DE-588)4055916-6 gnd Anwendung (DE-588)4196864-5 gnd Multivariate Analyse (DE-588)4040708-1 gnd Entscheidungstheorie (DE-588)4138606-1 gnd |
topic_facet | Statistik Statistics Bayes-Entscheidungstheorie Sozialwissenschaften Anwendung Multivariate Analyse Entscheidungstheorie |
url | http://www.loc.gov/catdir/enhancements/fy0709/99032699-d.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015697768&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
work_keys_str_mv | AT stevensjamesp intermediatestatisticsamodernapproachsasspss |