IBM SPSS statistics 19 made simple:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Hove [u.a.]
Psychology Press
2012
|
| Ausgabe: | 1. publ. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | XIV, 671 S. Ill., graph. Darst. |
| ISBN: | 9781848720695 1848720696 |
Internformat
MARC
| LEADER | 00000nam a2200000 c 4500 | ||
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| 008 | 110725s2012 xx ad|| |||| 00||| eng d | ||
| 020 | |a 9781848720695 |c pbk. |9 978-1-84872-069-5 | ||
| 020 | |a 1848720696 |9 1-84872-069-6 | ||
| 035 | |a (OCoLC)690089866 | ||
| 035 | |a (DE-599)BVBBV039157179 | ||
| 040 | |a DE-604 |b ger |e rakwb | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-83 |a DE-473 |a DE-11 | ||
| 082 | 0 | |a 005.5/5 |2 23 | |
| 084 | |a ST 601 |0 (DE-625)143682: |2 rvk | ||
| 100 | 1 | |a Gray, Colin D. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a IBM SPSS statistics 19 made simple |c Colin D. Gray & Paul R. Kinnear |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a Hove [u.a.] |b Psychology Press |c 2012 | |
| 300 | |a XIV, 671 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Includes bibliographical references and index | ||
| 650 | 0 | 7 | |a SPSS |0 (DE-588)4056588-9 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Statistisches Modell |0 (DE-588)4121722-6 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Statistisches Modell |0 (DE-588)4121722-6 |D s |
| 689 | 0 | 1 | |a SPSS |0 (DE-588)4056588-9 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Kinnear, Paul R. |e Verfasser |4 aut | |
| 856 | 4 | 2 | |m Digitalisierung UB Bamberg |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024174794&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-024174794 | |
Datensatz im Suchindex
| _version_ | 1817681161207414784 |
|---|---|
| adam_text |
Contents
Preface
xiii
CHAPTER
1
INTRODUCTION
1
1.1 AIMS AND OBJECTIVES
/
1.
2
MEASUREMENTS AND DATA
2
1
.2.1
Variables: quantitative and qualitative
2
1.2.2
Levels of measurement: scale, ordinal and nominal data
2
1.2.3
Univariate, bivariate and multivariate data sets
3
1.3
DISTRIBUTIONS
4
1
.3.1
The three most important properties of a distribution
5
1.3.2
Some common distribution shapes
6
1
.4
EXPERIMENTAL VERSUS CORRELATIONAL RESEARCH
7
1.4.1
A simple experiment
8
1.4.2
A more complex experiment
9
1.4.3
A correlational study
10
1.4.4
Quasi-experiments
13
1
.5
CHOOSING A STATISTICAL TEST
13
1.5.1
Considerations in choosing a statistical test
13
1.5.2
Five common research situations
14
1.6
A SIGNIFICANT DIFFERENCE?
15
1.6.1
Independent or related samples?
75
1.6.2
Flow chart
16
1
.7
ARE TWO VARIABLES ASSOCIATED?
17
1.7.1
Flowchart/«
1.7.2
Measuring association in ordinal data
18
1.7.3
Measuring association in nominal data: contingency tables
19
1.7.4
Multi-way contingency tables
20
1
.8
MAKING PREDICTIONS
20
1.8.1
Flow chart
20
1.8.2
Simple regression
21
1.8.3
Multiple regression
21
1.8.4
Predicting category membership
22
1
.9
FROM A SINGLE SAMPLE TO THE POPULATION
22
1.9.1
Flow chart
22
1.9.2
Goodness-of-fit: nominal data
23
1.9.3
Inferences about the mean of a single population
23
1.10
THE SEARCH FOR LATENT VARIABLES
24
1.11
MULTIVARIATE STATISTICS
24
111
¡v
Contents
1.12
A FINAL WORD
25
CHAPTER
2
Getting started with IBM SPSS Statistics
19 26
2.
1 INTRODUCTION
26
2.2
DESCRIBING THE DATA FROM THE CAFFEINE EXPERIMENT
29
2.2.1
Opening SPSS
29
2.2.2
The SPSS Statistics Data Editor
30
2.2.3
Working in Variable View
30
2.2.4
Working in Data View
35
2.2.5
Computing the group means
39
2.2.6
The SPSS Statistics Viewer
42
2.2.7
The output from the Means procedure
46
2.2.8
Histograms
47
2.2.9
Editing items in the Viewer
52
2.2.10
Ending the session
53
2.2.11
Resuming work on a saved data set
53
2.3
THE FOUR DRUGS EXPERIMENT
53
2.3.1
In Variable View
54
2.3.2
In Data View
56
2.3.3
Using the Means procedure
57
2.3.4
The histograms
59
2.4
PRINTING FROM THE STATISTICS VIEWER
60
2.5
USING SPSS SYNTAX
64
2.5.1
The Syntax Editor
65
2.5.2
Running the Means procedure with Syntax
66
2.5.3
Looping functions in Syntax
69
2.6
A FINAL WORD
69
CHAPTER
3
Editing data sets
70
3.1
MORE ON THE DATA EDITOR
70
3.1.1
A preliminary check on the default settings
70
3.1.2
Inserting new variables
71
3.1.3
Rearranging the order of variables in the Data Editor
72
3.1.4
Inserting case numbers
73
3.1.5
Using Syntax to insert case numbers into a data set
76
3.1.6
Inserting case numbers into an empty Data Editor
76
3.1.7
Using Syntax to insert case numbers into an empty Data Editor
77
3.1.8
Changing the default settings for Width and Decimals
77
3.1.9
String variables
78
3.1.10
Specifying missing values
80
3.1.11
Changing the Alignment settings
82
3.1.12
Opening an SPSS file
82
3.1.13
Entering data from other applications
83
3.1.14
Creating new variables while in Data View
84
3.1.15
Adding new cases while in Data View
85
3.2
VALIDATION OF THE DATA
85
Contents
3.2.1
Validation
of the data by defining rules
85
3.2.2
Handling multiple duplications in a large data set
91
3.3
ĽDITING
ITEMS IN THE VIEWER
92
3.3.1
Changing the format of a table
92
3.3.2
Widening, narrowing and hiding columns in a Report table
94
3.3.3
Deleting rows and columns from a Report table
95
3.3.4
Editing the captions in a table
96
3.3.5
Changing the number of decimal places displayed in a table
97
3.4
SELECTING CASES
97
3.5
AGGREGATING DATA
99
3.6
SORTING DATA
101
3.7
FILE-MERGING: ADDING CASES
103
3.8
FILE-MERGING: ADDING VARIABLES
105
3.9
THE COMPUTE VARIABLE COMMAND
108
3.9.1
Calculating functions of several variables
108
3.9.2
Conditional transformations
109
3.10
THE
RECODE
COMMAND
//2
3.11
A FINAL WORD
//5
CHAPTER
4
Describing and exploring your data
117
4.
1 INTRODUCTION
117
4.2
DESCRIBING NOMINAL DATA
119
4.2.1
Describing nominal data on one attribute
119
4.2.2
Two attributes: contingency tables
121
4.3
DESCRIBING CONTINUOUS OR SCALE DATA
130
4.3.1
Histograms of height and weight for males and
females
131
4.3.2
Obtaining scatterplots of weight against height
132
4.3.3
Statistics of height in males and females
/35
4.4
DESCRIBING SMALL DATA SETS
137
4.4.1
The stem-and-leaf display and the boxplot
138
ЛА2
Exploring a small data set
142
4.4.3
Some of the statistical output from Explore
143
4.5
DESCRIBING DATA FROM MULTIPLE RESPONSE QUESTIONNAIRES
145
4.5.1
Data for the Multiple Response procedure
147
4.5.2
Creating a multiple response set
148
4.5.3
Obtaining the crosstabulations
150
4.5.4
Finding the frequencies of specific transport profiles
755
4.6
A FINAL WORD
159
CHAPTER
5
More on graphs and charts
161
5.
1 INTRODUCTION
161
5.2
BAR CHARTS
162
5.2.1
Simple bar charts
162
5.2.2
Clustered bar charts
163
5.2.3
Panelled bar charts
166
vi
Contents
5.2.5
Editing a bar
chart
167
5.3
ERROR BAR CHARTS
171
5.4
BOXPLOTS
173
5.5
PIE
CHARTS
/75
5.6
LINE
GRAPHS
174
5.6.1
The Visual Binning procedure
175
5.6.2
Plotting line graphs
177
5.7
USING CHART TEMPLATES
179
5.8
A FINAL WORD
183
CHAPTER
6
Comparing averages: Two-sample and one-
sample tests
184
6.
1 OVERVIEW
Ш
6.2
THE INDEPENDENT-SAMPLES
Τ
TEST WITH SPSS
185
6.2.1
Running the
t
test
185
6.2.2
Interpreting the output
188
6.2.3
Two-tailed and one-tailedp-values
190
6.2.4
Measuring effect size
191
6.2.5
Reporting the results of a statistical test
193
6.3
THE RELATED-SAMPLES (OR PAIRED-SAMPLES)
T
TEST
194
6.3.1
Preparing the data file
195
6.3.2
Exploring the data
195
6.3.3
Running the
/
test
196
6.3.4
Interpreting the output
197
6.3.5
Measuring effect size
198
6.3.6
Reporting the results of the test
199
63
Л
A one-sample test
199
6.4
NONPARAMETRIC TESTS
199
6.4.1
Nonparametric tests in SPSS
200
6.4.2
Independent samples: The Mann-Whitney
U
test
201
6.4.3
Output from the Mann-Whitney
U
test
203
6.4.4
Exact tests
206
6.4.5
Effect size
207
6.4.6
The report
208
6.5
THE WILCOXON MATCHED-PAIRS TEST
209
6.5.1
The Wilcoxon matched-pairs tests in SPSS
209
6.5.2
The output
210
6.5.3
Effect size
214
6.5.4
The report
215
6.6
THE SIGN AND BINOMIAL TESTS
215
6.6.1
The sign test in SPSS
216
6.6.2
Bernoulli trials: the binomial test
219
6.7
EFFECT SIZE, POWER AND NUMBER OF PARTICIPANTS
223
6.8
A FINAL WORD
225
Contents_
CHAPTER
7
The one-way
ANOVA 221
7.1
INTRODUCTION
227
7.2
ENTKRING
TI
IE DATA
233
7.3
RUNNING THE ONE-WAY ANOVA ON GEM
236
7.3.1
Finding the GLM menu
236
7.3.2
Descriptives
and the ANOVA summary table
241
7.3.3
The profile plot
243
7.3.4
Measuring effect size
244
7.3.5
Report of the analysis
246
7.4
MAKING COMPARISONS AMONG THE TREATMENT MEANS
24',
7.4.1
Planned and unplanned comparisons
247
ΊΑ.2
Linear contrasts
251
7.4.3
Helmert contrasts
252
7.5
POWER AND EFFECT SIZE IN THE ONE-WAY ANOVA
258
7.6
ALTERNATIVES TO THE ONE-WAY ANOVA
260
1.1
A FINAL WORD
266
CHAPTER
б
Between subjects factorial experiments
268
8.1
INTRODUCTION
268
8.1.1
An experiment with two treatment factors
268
8.1.2
Main effects and interactions
270
8.1.3
Profile plots
277
8.2
HOW
'ГНЕ
TWO-WAY ANOVA WORKS
272
8.2.1
The two-way ANOVA
272
8.2.2
Degrees of freedom
273
8.2.3
The two-way ANOVA summary table
274
8.3
THE TWO-WAY ANOVA WITH SPSS
275
8.3.1
Entering the data
2 76
8.3.2
Exploring the data: boxplots
277
8.3.3
Choosing a factorial ANOVA
277
8.3.4
Output for a factorial ANOVA
280
8.3.5
Measuring effect size in the two-way ANOVA
282
8.3.6
Reporting the results of the two-way ANOVA
285
8.4
FURTHER ANALYSIS
286
8.4.1
A problem with multiple comparisons
286
8.4.2
Unpacking significant main effects: post hoc tests
286
8.4.3
The analysis of interactions
287
8.5
TESTING FOR SIMPLE MAIN EFFECTS WITH SYNTAX
289
8.5.1
Using the
MÁNOVA
command to run the univariate ANOVA
289
8.5.2
Including simple effects in a MANOVA command
291
8.6
HOW MANY PARTICIPANTS SHALL I NEED?
297
8.7
MORE COMPLEX EXPERIMENTS
298
8.7.1
Three-way interactions
298
8.7.2
The three-way ANOVA
299
8.7.3
How the three-way ANOVA works
301
8.7
'A The three-way ANOVA with SPSS
302
viii Contents
8.7.5
Follow-up analysis following a significant three-way interaction
304
8.7.6
Testing for simple interactions and simple, simple main effects
305
8.7.7
Unplanned multiple comparisons
308
8.8
A FINAL WORD
309
CHAPTER
9
Within subjects experiments
311
9.
1 INTRODUCTION
311
9.1.1
Rationale of a within subjects experiment
311
9.1.2
How the within subjects
ANO VA
works
312
9.1.3
A within subjects experiment on the effect of target shape on shooting
accuracy
315
9.1.4
Order effects
:
counterbalancing
316
9.1.5
Assumptions underlying the within subjects ANOVA: homogeneity of
covariance
317
9.2
A ONE-FACTOR WITHIN SUBJECTS ANOVA WITH SPSS
318
9.2.1
Entering the data
319
9.2.2
Running the one-factor within subjects ANOVA
319
9.2.3
Output for a one-factor within subjects ANOVA
322
9.2.4
Effect size in the within subjects ANOVA
327
9.3
HOW MANY PARTICIPANTS SHALL I NEED?
328
9.4
NONPARAMETRIC EQUIVALENTS OF THE WITHIN SUBJECTS ANOVA
329
9.4.1
The Friedman test for ordinal data
329
9.4.2
Cochran's
Q
test for nominal data
333
9.5
THE TWO-FACTOR WITHIN SUBJECTS ANOVA
336
9.5.1
Preparing the data set
337
9.5.2
Running the two-factor within subjects ANOVA
338
9.5.3
Output for a two-factor within subjects ANOVA
341
9.5.4
Unpacking a significant interaction with multiple comparisons
344
9.6
A FINAL WORD
346
CHAPTER
10
Mixed factorial experiments
349
I O.I INTRODUCTION
349
10.1.1
A mixed factorial experiment
349
10.1.2
Classifying mixed factorial designs
35/
10.1.3
Rationale of the mixed ANOVA
351
10.2
THE TWO-FACTOR MIXED FACTORIAL ANOVA WITH SPSS
354
10.2.1
Preparing the SPSS data set
354
10.2.2
Running the ANOVA
355
10.2.3
Output for the two-factor mixed ANOVA
357
10.2.4
Simple effects analysis with syntax
364
1 0.3
THE THREE-FACTOR MIXED ANOVA
369
10.3.1
The two three-factor mixed designs
369
10.3.2
Two within subjects factors
370
10.3.3
Using syntax to test for simple effects
375
10.3.4
One within subjects factor and two between subjects factors: the AxBx(C)
mixed factorial design
380
Contents ¡x
10.4
THE MULTIVARIATE ANALYSIS OF VARIANCE
(MÁNOVA)
387
10.4.1
What the
MÁNOVA
does
387
10.4.2
How the
MÁNOVA
works
389
10.4.3
Assumptions of the
MÁNOVA
392
10.4.4
Application of the
MÁNOVA
to the shape recognition experiment
393
10.5
A FINAL WORD
397
CHAPTER
11
Measuring statistical association
399
ILI
INTRODUCTION
399
11.1.1
A correlational study
400
11.1.2
Linear relationships
401
I
1.2
THE PEARSON CORRELATION
402
11.2.1
Formula for the Pearson correlation
402
11.2.2
The range of values of the Pearson correlation
403
11.2.3
The sign of a correlation
404
11.2.4
Testing an obtained value of
r
for significance
405
11.2.5
A word of warning about the correlation coefficient
405
11.2.6
Effect size
406
1
1
.3
CORRELATION WITH SPSS
407
1.3.1
Preparing the SPSS data set
407
1.3.2
Obtaining the scatterplot
408
11.3.3
Obtaining the Pearson correlation
408
1.3.4
Output for the Pearson correlation
408
I
1.4
OTHER MEASURES OF ASSOCIATION
409
1.4.1
Spearman's rank correlation
409
1.4.2
Kendall's
tau
statistics
410
1
1.4.3
Rank correlations with SPSS
411
11.5
NOMINAL DATA
412
11.5.1
The one-sample approximate chi-square goodness-of-fit test with three or more
categories
413
11.5.2
Running a chi-square goodness-of-fit test on SPSS
414
11.5.3
Measuring effect size following a chi-square test of goodness-of-fit
418
11.5.4
Testing for association between two qualitative variables in a contingency
table
420
11.5.5
Analysis of contingency tables with SPSS
425
11.5.6
Getting help with the output
43
J
11.5.7
Some cautions and caveats
432
11.5.8
Other problems with traditional chi-square analyses
440
1
1
.6
DO DOCTORS AGREE? COHEN'S KAPPA
440
1 1.7
PARTIAL CORRELATION
443
IÌ.9
A FINAL WORD
447
CHAPTER
12
Regression
448
1
2.
1 INTRODUCTION-MS'
1
2.
1
.
1 Simple, two-variable regression
449
1
2.
1.
2
Residuatelo
Contents
12.1.3
The least squares criterion for 'the best-fitting line'
451
12.1.4
Regression and correlation
452
12.1.5
The coefficient of determination revisited
453
12.1.6
Shrinkage with resampling: cross-validation
455
12.1.7
Beta coefficients
456
12.1.8
Effects of linear transformations on correlation and regression
coefficients
458
12.2
SIMPLE REGRESSION WITH SPSS
458
12.2.1
Drawing scatterplots with regression lines
458
12.2.2
The output for simple regression
464
12.3
MULTIPLE REGRESSION
469
12.3.1
The multiple regression equation
469
12.3.2
Partial and semipartial (part) correlations
471
12.3.3
Measuring the importance of an IV in multiple regression
473
12.3.4
Strategies in multiple regression
474
12.4
MULTIPLE REGRESSION WITH SPSS
475
12.4.1
Running a simultaneous multiple regression with SPSS
475
12.4.2
The output from simultaneous multiple regression
478
12.4.3
An hierarchical multiple regression
482
12.5
RUNNING THE ANOVA AS A MULTIPLE REGRESSION
486
12.5.1
The two-group case
486
12.5.2
The k-group case
492
12.5.3
Other systems of coding: contrast coding and effects coding
498
12.5.4
The factorial ANOVA as a regression
499
12.6
MULTILEVEL REGRESSION MODELS
503
12.7
A FINAL WORD
504
CHAPTER
13
The analysis of covariance (ANCOVA)
507
13.
1 INTRODUCTION
505
13.2
THE ANCOVA WITH SPSS
508
13.2.1
Preliminary analysis
508
13.2.2
The five within groups regression lines
509
13.2.3
The ANCOVA
577
13.2.4
Further analysis
513
13.3
THE ANCOVA AS AN HIERARCHICAL MULTIPLE REGRESSION
518
13.3.1
Setting up the regression
519
13.3.2
Running the regression
520
13.3.3
Interpreting the output
522
13.4
A FACTORIAL ANCOVA
525
13.5
A FINAL WORD
529
CHAPTER
14
Analyses of multiway frequency tables
531
14.
1 INTRODUCTION
531
14.2
SOME BASICS OF
LOGLINEAR
MODELLING
532
14.2.1 Loglinear
models and ANOVA models
532
W
2,2
Model-building and the hierarchical principle
534
Contents xi
14.2.3
The main-effects-only
loglinear
model and the traditional chi-square test for
association
536
14.2.4
Analysis of the residuals
537
14.3
MODHLLING A TWO-WAY CONTINGKNCY TABLE 53<S
14.3.1
SPSS procedures for
loglinear
analysis
538
14.3.2
Fitting an unsaturated model
543
14.3.3
Summary
548
14.4
MODELLING A THREE-WAY FREQUENCY TABLE 54H
14.4.1
Exploring the data
549
14.4.2
Loglinear analysis of the data on gender and helpfulness
550
14.4.3
The main-effects-only model and the traditional chi-square test
555
14.4.4
Collapsing a multi-way table: the requirement of conditional independence
557
14.4.5
An alternative data set for the gender and helpfulness experiment
558
14.4.6
Reporting the results of a loglinear analysis
561
14.5
Λ
FINAL WORD
562
CHAPTER
15
Predicting category membership: logistic
regression
564
1
5.
1 INTRODUCTION
564
15.1.1
Logistic regression
565
15.1.2
Binary and multinomial logistic regression
565
15.2
BINARY LOGISTIC REGRESSION
566
15.2.1
How logistic regression works
568
15.2.2
A binary logistic regression with quantitative variables
574
15.2.3
A binary logistic regression with categorical independent variables
584
15.3
MULTINOMIAL LOGISTIC REGRESSION 5H8
15.3.1
Accessing the data set
589
15.3.2
Running multinomial logistic regression
590
15.5
A FINAL WORD
599
CHAPTER
16
The search for latent variables: factor analysis
601
1
6.
1 INTRODUCTION
601
16.1.1
Stages in an exploratory factor analysis
603
16.1.2
The extraction of factors
604
16.1.3
The rationale of rotation
604
16.1.4
Some issues in factor analysis
604
16.1.5
Some key technical terms
605
16.1.6
Preliminaries
606
16.2
AN EXPLORATORY FACTOR ANALYSIS
607
16.2.1
Entering the data for a factor analysis
607
16.2.2
Running a factor analysis on SPSS
608
16.2.3
Output for factor analysis
610
16.3
USING SPSS SYNTAX TO RUN AN EXPLORATORY FACTOR ANALYSIS
619
16.3.1
Procedure with the raw data as input
619
16.3.2
Procedure with a correlation matrix as input
620
xii Contents
16.3.3
Progressing with SPSS syntax
624
16.4
A FINAL WORD
626
Appendix
628
Glossary
637
References
654
Index
656 |
| any_adam_object | 1 |
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| bvnumber | BV039157179 |
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| dewey-full | 005.5/5 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
| dewey-raw | 005.5/5 |
| dewey-search | 005.5/5 |
| dewey-sort | 15.5 15 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| edition | 1. publ. |
| format | Book |
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| id | DE-604.BV039157179 |
| illustrated | Illustrated |
| indexdate | 2024-12-06T09:03:58Z |
| institution | BVB |
| isbn | 9781848720695 1848720696 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-024174794 |
| oclc_num | 690089866 |
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| physical | XIV, 671 S. Ill., graph. Darst. |
| publishDate | 2012 |
| publishDateSearch | 2012 |
| publishDateSort | 2012 |
| publisher | Psychology Press |
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| spelling | Gray, Colin D. Verfasser aut IBM SPSS statistics 19 made simple Colin D. Gray & Paul R. Kinnear 1. publ. Hove [u.a.] Psychology Press 2012 XIV, 671 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references and index SPSS (DE-588)4056588-9 gnd rswk-swf Statistisches Modell (DE-588)4121722-6 gnd rswk-swf Statistisches Modell (DE-588)4121722-6 s SPSS (DE-588)4056588-9 s DE-604 Kinnear, Paul R. Verfasser aut Digitalisierung UB Bamberg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024174794&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Gray, Colin D. Kinnear, Paul R. IBM SPSS statistics 19 made simple SPSS (DE-588)4056588-9 gnd Statistisches Modell (DE-588)4121722-6 gnd |
| subject_GND | (DE-588)4056588-9 (DE-588)4121722-6 |
| title | IBM SPSS statistics 19 made simple |
| title_auth | IBM SPSS statistics 19 made simple |
| title_exact_search | IBM SPSS statistics 19 made simple |
| title_full | IBM SPSS statistics 19 made simple Colin D. Gray & Paul R. Kinnear |
| title_fullStr | IBM SPSS statistics 19 made simple Colin D. Gray & Paul R. Kinnear |
| title_full_unstemmed | IBM SPSS statistics 19 made simple Colin D. Gray & Paul R. Kinnear |
| title_short | IBM SPSS statistics 19 made simple |
| title_sort | ibm spss statistics 19 made simple |
| topic | SPSS (DE-588)4056588-9 gnd Statistisches Modell (DE-588)4121722-6 gnd |
| topic_facet | SPSS Statistisches Modell |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024174794&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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