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E-raamat: IBM SPSS Statistics 27 Step by Step: A Simple Guide and Reference

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  • Formaat: 404 pages
  • Ilmumisaeg: 28-Dec-2021
  • Kirjastus: Routledge
  • Keel: eng
  • ISBN-13: 9781000486858
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IBM SPSS Statistics 27 Step by Step: A Simple Guide and ReferenceSuurem pilt
  • Formaat: 404 pages
  • Ilmumisaeg: 28-Dec-2021
  • Kirjastus: Routledge
  • Keel: eng
  • ISBN-13: 9781000486858
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IBM SPSS Statistics 27 Step by Step: A Simple Guide and Reference, seventeenth edition, takes a straightforward, step-by-step approach that makes SPSS software clear to beginners and experienced researchers alike. Extensive use of four-color screen shots, clear writing, and step-by-step boxes guide readers through the program. Output for each procedure is explained and illustrated, and every output term is defined. Exercises at the end of each chapter support students by providing additional opportunities to practice using SPSS.

This book covers the basics of statistical analysis and addresses more advanced topics such as multidimensional scaling, factor analysis, discriminant analysis, measures of internal consistency, MANOVA (between- and within-subjects), cluster analysis, Log-linear models, logistic regression, and a chapter describing residuals. The end sections include a description of data files used in exercises, an exhaustive glossary, suggestions for further reading, and a comprehensive index.

IBM SPSS Statistics 27 Step by Step is distributed in 85 countries, has been an academic best seller through most of the earlier editions, and has proved an invaluable aid to thousands of researchers and students.

New to this edition:





Screenshots, explanations, and step-by-step boxes have been fully updated to reflect SPSS 27 A new chapter on a priori power analysis helps researchers determine the sample size needed for their research before starting data collection.
Preface xii
1 An Overview of IBM® SPSS® Statistics
1(7)
Introduction: An Overview of IBM SPSS Statistics 27 and Subscription Classic
1(1)
1.1 Necessary Skills
1(1)
1.2 Scope of Coverage
2(1)
1.3 Overview
3(1)
1.4 This Book's Organization,
Chapter by
Chapter
3(1)
1.5 An Introduction to the Example
4(1)
1.6 Typographical and Formatting Conventions
5(3)
2A IBM SPSS Statistics Processes for PC
8(18)
2.1 The Mouse
8(1)
2.2 The Taskbar and Start Menu
8(2)
2.3 Common Buttons
10(1)
2.4 The Data and Other Commonly Used Windows
10(3)
2.5 The Open Data File Dialog Window
13(3)
2.6 The Output Window
16(3)
2.7 Modifying or Rearranging Tables
19(3)
2.8 Printing or Exporting Output
22(2)
2.9 The "Options ..." Option: Changing the Formats
24(2)
2B IBM SPSS Statistics Processes for Mac
26(17)
2.1 Selecting
26(1)
2.2 The Desktop, Dock, and Application Folder
27(1)
2.3 Common Buttons
27(1)
2.4 The Data and Other Commonly Used Windows
28(2)
2.5 The Open Data File Dialog Window
30(3)
2.6 The Output Window
33(3)
2.7 Modifying or Rearranging Tables
36(3)
2.8 Printing or Exporting Output
39(2)
2.9 The "Options ..." Option: Changing the Formats
41(2)
3 Creating and Editing a Data File
43(16)
3.1 Research Concerns and Structure of the Data File
43(1)
3.2 Step by Step
44(7)
3.3 Entering Data
51(1)
3.4 Editing Data
52(2)
3.5 Grades.sav: The Sample Data File
54(5)
Exercises
58(1)
4 Managing Data
59(24)
4.1 Step By Step: Manipulation of Data
60(1)
4.2 The Case Summaries Procedure
60(3)
4.3 Replacing Missing Values Procedure
63(3)
4.4 The Compute Procedure: Creating New Variables
66(3)
4.5 Recoding Variables
69(4)
4.6 The Select Cases Option
73(2)
4.7 The Sort Cases Procedure
75(2)
4.8 Merging Files Adding Blocks of Variables or Cases
77(4)
4.9 Printing Results
81(2)
Exercises
82(1)
5 Graphs and Charts: Creating and Editing
83(18)
5.1 Comparison of the Two Graphs Options
83(1)
5.2 Types of Graphs Described
83(1)
5.3 The Sample Graph
84(1)
5.4 Producing Graphs and Charts
85(2)
5.5 Bugs
87(1)
5.6 Specific Graphs Summarized
88(11)
5.7 Printing Results
99(2)
Exercises
100(1)
6 Frequencies
101(11)
6.1 Frequencies
101(1)
6.2 Bar Charts
101(1)
6.3 Histograms
101(1)
6.4 Percentiles
102(1)
6.5 Step by Step
102(6)
6.6 Printing Results
108(1)
6.7 Output
108(4)
Exercises
111(1)
7 Descriptive Statistics
112(9)
7.1 Statistical Significance
112(1)
7.2 The Normal Distribution
113(1)
7.3 Measures of Central Tendency
114(1)
7.4 Measures of Variability Around the Mean
114(1)
7.5 Measures of Deviation from Normality
114(1)
7.6 Measures of Size of the Distribution
115(1)
7.7 Measures of Stability: Standard Error
115(1)
7.8 Step by Step
115(4)
7.9 Printing Results
119(1)
7.10 Output
119(2)
Exercises
120(1)
8 Crosstabulation and X2 Analyses
121(11)
8.1 Crosstabulation
121(1)
8.2 Chi-Square (xa) Tests of Independence
121(2)
8.3 Step by Step
123(4)
8.4 Weight Cases Procedure: Simplified Data Setup
127(2)
8.5 Printing Results
129(1)
8.6 Output
129(3)
Exercises
131(1)
9 The Means Procedure
132(7)
9.1 Step by Step
132(4)
9.2 Printing Results
136(1)
9.3 Output
136(3)
Exercises
138(1)
10 A Priori Power Analysis: What Sample Size Do I Need?
139(12)
10.1 One-Sample t Test
141(1)
10.2 Independent-Samples t Test
142(1)
10.3 Paired-Samples t Test
143(1)
10.4 One-Way ANOVA
144(2)
10.5 Correlation
146(1)
10.6 Regression
147(1)
10.7 Printing Results
148(3)
Exercises
149(2)
11 Bivariate Correlation
151(10)
11.1 What is a Correlation?
151(2)
11.2 Additional Considerations
153(1)
11.3 Step by Step
154(4)
11.4 Printing Results
158(1)
11.5 Output
159(2)
Exercises
160(1)
12 The t Test Procedure
161(12)
12.1 Independent-Samples t Tests
161(1)
12.2 Paired-Samples t Tests
161(1)
12.3 One-Sampler Tests
162(1)
12.4 Significance and Effect Size
162(1)
12.5 Step by Step
163(4)
12.6 Printing Results
167(1)
12.7 Output
168(5)
Exercises
171(1)
What is Bootstrapping?
172(1)
13 The One-Way ANOVA Procedure
173(12)
13.1 Introduction to One-Way Analysis of Variance
173(1)
13.2 Step by Step
174(5)
13.3 Printing Results
179(1)
13.4 Output
179(6)
Exercises
183(2)
14 General Linear Model: Two-Way ANOVA
185(8)
14.1 Statistical Power
185(1)
14.2 Two-Way Analysis of Variance
186(1)
14.3 Step by Step
187(3)
14.4 Printing Results
190(1)
14.5 Output
190(3)
Exercises
192(1)
15 General Linear Model: Three-Way ANOVA
193(16)
15.1 Three-Way Analysis of Variance
193(1)
15.2 The Influence of Covariates
194(1)
15.3 Step by Step
195(2)
15.4 Printing Results
197(1)
15.5 Output
197(5)
15.6 A Three-Way ANOVA that Includes a Covariate
202(7)
Exercises
206(3)
16 Simple Linear Regression
209(15)
16.1 Predicted Values and the Regression Equation
209(2)
16.2 Simple Regression and the Amount of Variance Explained
211(1)
16.3 Testing for a Curvilinear Relationship
211(3)
16.4 Step by Step
214(4)
16.5 Printing Results
218(1)
16.6 Output
219(1)
16.7 A Regression Analysis that Tests for a Curvilinear Trend
220(4)
Exercises
221(3)
17 Multiple Regression Analysis
224(14)
17.1 The Regression Equation
224(2)
17.2 Regression and R2: The Amount of Variance Explained
226(1)
17.3 Curvilinear Trends, Model Building, and References
226(2)
17.4 Step by Step
228(5)
17.5 Printing Results
233(1)
17.6 Output
233(1)
17.7 Change of Values as Each new Variable is Added
234(4)
Exercises
237(1)
18 Nonparametric Procedures
238(13)
18.1 Step by Step
239(2)
18.2 Are Observed Values Distributed Differentiy than a Hypothesized Distribution?
241(2)
18.3 Is the Order of Observed Values Non-Random?
243(1)
18.4 Is a Continuous Variable Different in Different Groups?
244(2)
18.5 Are the Medians of a Variable Different for Different Groups?
246(1)
18.6 Are My Within-Subjects (Dependent Samples or Repeated Measures) Measurements Different?
247(3)
18.7 Printing Results
250(1)
19 Reliability Analysis
251(12)
19.1 Coefficient Alpha (α)
252(1)
19.2 Split-Half Reliability
252(1)
19.3 The Example
252(1)
19.4 Step by Step
253(4)
19.5 Printing Results
257(1)
19.6 Output
257(6)
Exercises
262(1)
20 Multidimensional Scaling
263(11)
20.1 Square Asymmetrical Matrixes (The Sociogram Example)
264(1)
20.2 Step by Step
265(6)
20.3 Printing Results
271(1)
20.4 Output
271(3)
21 Factor Analysis
274(13)
21.1 Create a Correlation Matrix
274(1)
21.2 Factor Extraction
274(1)
21.3 Factor Selection and Rotation
275(2)
21.4 Interpretation
277(1)
21.5 Step by Step
278(6)
21.6 Output
284(3)
22 Cluster Analysis
287(14)
22.1 Cluster Analysis and Factor Analysis Contrasted
287(1)
22.2 Procedures for Conducting Cluster Analysis
288(2)
22.3 Step by Step
290(6)
22.4 Printing Results
296(1)
22.5 Output
296(5)
23 Discriminant Analysis
301(15)
23.1 The Example: Admission into a Graduate Program
302(1)
23.2 The Steps Used in Discriminant Analysis
302(2)
23.3 Step by Step
304(5)
23.4 Output
309(7)
24 General Linear Models: MANOVA and MANCOVA
316(15)
24.1 Step by Step
317(7)
24.2 Printing Results
324(1)
24.3 Output
325(6)
Exercises
330(1)
25 G.L.M.: Repeated-Measures MANOVA
331(11)
25.1 Step by Step
332(5)
25.2 Printing Results
337(1)
25.3 Output
337(5)
Exercises
341(1)
26 Logistic Regression
342(10)
26.1 The Math of Logistic Regression
342(1)
26.2 Step by Step
343(4)
26.3 Printing Results
347(1)
26.4 Output
348(4)
27 Hierarchical Log-Linear Models
352(12)
27.1 Log-Linear Models
352(1)
27.2 The Model Selection Log-Linear Procedure
353(1)
27.3 Step by Step
354(4)
27.4 Printing Results
358(1)
27.5 Output
358(6)
28 Nonhierarchical Log-Linear Models
364(9)
28.1 Models
364(1)
28.2 A Few Words about Model Selection
365(1)
28.3 Types of Models Beyond the Scope of This
Chapter
365(1)
28.4 Step by Step
366(4)
28.5 Printing Results
370(1)
28.6 Output
370(3)
29 Residuals: Analyzing Left-Over Variance
373(14)
29.1 Residuals
373(1)
29.2 Linear Regression: A Case Study
374(2)
29.3 General Log-Linear Models: A Case Study
376(4)
29.4 Accessing Residuals in SPSS
380(7)
Data Files
383(4)
Glossary 387(6)
References 393(2)
Credits 395(2)
Index 397
Darren George teaches at the University of Alabama. His research focuses on intimate relationships and optimal performance. He teaches classes in research methodology, statistics, personality/social psychology, and sport and performance psychology.

Paul Mallery is a Professor of Psychology at La Sierra University whose research focuses on the intersection of religion and prejudice. He teaches classes in research methodology, statistics, social psychology, and political psychology.
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