Understanding statistical analysis and modeling:
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Los Angeles ; London ; New Delhi ; Singapore ; Washington DC ; Mlebourne
SAGE
[2018]
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xxiii, 411 Seiten Illustrationen, Diagramme |
| ISBN: | 9781506317410 |
Internformat
MARC
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| 100 | 1 | |a Bruhl, Robert H. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Understanding statistical analysis and modeling |c Robert Bruhl (University of Illinois at Chicago) |
| 264 | 1 | |a Los Angeles ; London ; New Delhi ; Singapore ; Washington DC ; Mlebourne |b SAGE |c [2018] | |
| 264 | 4 | |c © 2018 | |
| 300 | |a xxiii, 411 Seiten |b Illustrationen, Diagramme | ||
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Datensatz im Suchindex
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| adam_text | BRIEF CONTENTS
Introduction xvii
Acknowledgments xxi
About the Author xxiii
PART I • RESEARCH DESIGN l
Chapter t • “Why” Conduct Research, and “Why”
Use Statistics? 5
Chapter 2 • Methods of Quantitative Empirical
Investigation 27
PART II • DESCRIPTIVE STATISTICS 41
Chapter 3 • The Frequency Distribution Report: 4-3
Organizing a Set of Observations
Chapter^ • The Mode, the Median, and the Mean: 81
Describing a Typical Value of a Quantitative
Property Observed for a Set of Phenomena
Chapter 5 • The Variance and the Standard Deviation: 111
Describing the Variability Observed for a
Quantitative Property of a Set of Phenomena
Chapter 6 • The z-Transformation and Standardization: 159
Using the Standard Deviation to
Compare Observations
PART III • STATISTICAL INFERENCE
AND PROBABILITY 177
Chapter 7 • The Concept of a Probability 181
Chapter 8 • Coexisting Properties and Joint
Probability Models 209
Chapter 9 • Sampling and the Normal
Probability Model 233
PART IV • TOOLS FOR MAKING
STATISTICAL INFERENCES 271
Chapter 10 • Estimation Studies: 275
Inferring the Parameters of a Population
from the Statistics of a Sample
Chapter 11 • Chi-Square Analysis: 299
investigating a Suspected Association
between Two Qualitative Properties
Chapter 12 • The f-Test of Statistical Significance: 327
Comparing a Quantitative Property
Assessed forTwo Different Groups
Chapter 13 • Analysis of Variance: 347
Comparing a Quantitative Property
Assessed for Several Different Groups
Chapter 14 • Correlation Analysis and Linear Regression: 367
Assessing the Covariability of Two
Quantitative Properties
Index ¿07
DETAILED CONTENTS
Introduction xvii
Acknowledgments xxf
About the Author xxiii
PART I • RESEARCH DESIGN l
Purpose: Making Sense of What We Observe 1
Deciding How to Represent Properties of a Phenomenon 2
Describing Differences or Explaining
Differences Between Phenomena? 2
Deciding How to Collect Observations 3
Chapter 1 • “Why Conduct Research, and
Why Use Statistics? 5
1.0 Learning Objectives 5
1.1 Motivation 5
1.2 Representation and Modeling 7
Differentiation and Variability 7
Observation is an Active Process of Cognition 7
Quantitative or “Scale” Assessments 9
Ordinal Scale Assessments 10
Qualitative Assessments 11
1.3 A Special Case: Investigating Subjective Behavior 12
1.4 Reasons for an Empirical Investigation 13
Descriptive Studies 13
Explanatory Studies 14
The Role of Theory in an Explanatory Investigation 16
Some Concluding Remarks on Explanatory Research 17
1.5 Summary 20
1.6 Exercises 23
1.7 Some Formal Terminology (Optional) 23
Chapter 2 • Methods of Quantitative Empirical Investigation 27
2.0 Learning Objectives 27
2.1 Motivation 27
2.2 Instrumentation: Choosing a Tool to
Assess a Property of interest 28
2.3 Limited Focus or Intent to Generalize 30
Case Studies 30
Estimation Studies 31
2.4 Controlled or Natural Observations 32
Experimental Studies 32
Observational Studies 35
2.5 Applied Versus Pure Research 35
2.6 Summary 37
2.7 Exercises 38
PART II • DESCRIPTIVE STATISTICS 41
Organizing and Describing a Set of Observations 41
Measuring the Variability in a Set of Observations 42
Describing a Set of Observations in
Terms of Their Variability 42
Chapter 3 • The Frequency Distribution Report: 43
Organizing a Set of Observations
3.0 Learning Objectives 43
3.1 Motivation: Comparing, Sorting, and Counting 44
3.2 Constructing a Sample Frequency Distribution
for a “Qualitative Property 45
The Frequency Distribution Report 46
The Relative Frequency Distribution Report 47
Pictorial Presentations of the Relative Frequency Distribution 49
Interpreting the Analysis 51
3.3 Constructing a Sample Frequency Distribution
for an “Ordinal” Property 52
The Frequency Distribution Report 54
The Relative Frequency Distribution Report 54
Pictorial Presentations of the Relative Frequency Distribution 55
Interpreting the Results 57
3.4 Some Important Technical Notes 58
Categories, Values, and Counts 58
One Phenomenon — OneVaLue 58
Central Tendencies, Averages, and Norms 58
Precision and Rounding 59
3.5 Summary 60
3.6 SPSS Tutorial 61
Coding 62
Data Entry 64
Data Analysis 71
3.7 Exercises 78
Chapter 4 • The Mode, the Median, and the Mean: 81
Describing a Typical Value of a Quantitative
Property Observed for a Set of Phenomena
4.0 Learning Objectives 81
4.1 Motivation 82
4.2 A Cautionary Note Regarding Quantitatively Assessed Properties 83
4.3 Constructing a Sample Frequency Distribution
for a Quantitative Property 86
The Frequency Distribution Report 87
The Relative Frequency Distribution Report 88
Pictorial Representations of the Relative Frequency Distribution 89
The Informational Content of the Relative Frequency
Distribution Report 91
4.4 identifying a Typical Phenomenon from a Set of Phenomena 93
4.5 Assessing and Using the Median of a Set of Observations 94
The Cumulative Relative Frequency Distribution Report 95
Pictorial Depictions of the Cumulative Relative
Frequency Distribution Report 97
4.6 Assessing and Using the Mean of a Set of Observations 99
The Mean of a Set of Observations and the Method of Moments 100
ATechnical Note on Assessing the Mean for a Set of Observations 103
4.7 Interpreting and Comparing the Mode, the Median, and the Mean 105
4.8 Summary 106
4.9 SPSS Tutorial 107
4.10 Exercises 108
Chapters • The Variance and the Standard Deviation: 111
Describing the Variability Observed for a Quantitative
Property of a Set of Phenomena
5.0 Learning Objectives 111
5.1 Motivation 112
Comparing the Highest and Lowest Observed Values 112
Variation Assessed Through One-To-One Comparisons 113
Variation Assessed Through Comparison with a Reference Point 113
5.2 A Case Example: The Frequency Distribution Report 115
5.3 The Range of a Set of Observations 117
5.4 The Mean Absolute Difference 118
5.5 The Variance and the Standard Deviation 121
A Model of Natural Variation 121
Variation Versus Differentiation 123
The Method of Moments and the Variance 124
The Standard Deviation 125
Assessing the Standard Deviation 126
5.6 Interpreting the Variance and the Standard Deviation 128
Variance or Standard Deviation? 128
Normal Variation or Differentiation? 128
5.7 Comparing the Mean Absolute Difference and the
Standard Deviation 131
5.8 A Useful Note on Calculating the Variance 131
5.9 A Note on Modeling and the Assumption of Variability 135
5.10 Summary 135
5.11 SPSS Tutorial 136
5.12 Exercises 149
5.13 The Method of Moments (Optional) 152
Comparing the Different Moments: An Example 153
5.14 A Distribution of “Squared Differences from a Mean (Optional) 157
Chapter 6 • The z-Transformation and Standardization: 159
Using the Standard Deviation to Compare Observations
6.0 Learning Objectives 159
6.1 Motivation 159
Comparing Two Phenomena Using the Standard Deviation 160
Comparing Each Phenomenon with the “Typical Phenomenon 160
The Standardized Frequency Distribution 161
6.2 Executing the z-Transformation 162
6.3 An Example 165
6.4 Summary 171
6.5 An Exercise 172
PART III • STATISTICAL INFERENCE
AND PROBABILITY 177
Why Probability Theory? 177
The Concept of a Probability 178
Predicting Events Involving Two Coexisting Properties 179
Sampling and the Normal Probability Model 179
Chapter 7 • The Concept of a Probability 181
7.0 Learning Objectives 181
7.1 Motivation 181
An Estimation Study 182
An Association Study 182
7.2 Uncertainty, Chance, and Probability 183
7.3 Selection Outcomes and Probabilities 183
7.4 Events and Probabilities 184
7.5 Describing a Probability Model for a Quantitative Property 188
The Probability Polygon 190
The Expected Value of a Random Variable 193
A Note on Calculating the Expected Value 196
The Expected Variation in a Random Variable 196
A Note on Calculating the Variance 202
The z-Transformation and Standardization 204
7.6 Summary 206
7.7 Exercises 208
Chapter 8 • Coexisting Properties
and Joint Probability Models 209
8.0 Learning Objectives 209
8.1 Motivation 209
8.2 Probability Models Involving Coexisting Properties 210
8.3 Models of Association, Conditional Probabilities, and Stochastic
Independence 213
8.4 Covariability in Two Quantitative Properties 216
Representing Coexisting Properties of a Phenomenon as an Interaction
The Covariance
218
219
8.5 Importance of Stochastic Independence and
Covariance in Statistical Inference 225
8.6 Summary 227
8.7 Exercises 229
Calculating a Covariance 229
Constructing a Probability Model of a Non-Association 231
Chapter 9 • Sampling and the Normal Probability Model 233
9.0 Learning Objectives 233
9.1 Motivation 233
9.2 Samples and Sampling 234
9.3 Bernoulli Trials and the Binomial Distribution 240
In a Single Trial 241
Two Trials 242
Three Trials 244
A Family of Binomial Distributions 246
9.4 Representing the Character of a Population 253
9.5 Predicting Potential Samples from a Known Population 253
9.6 The Normal Distribution 259
9.7 The Central Limit Theorem 262
9.8 Normal Sampling Variability and Statistical Significance 264
9.9 Summary 266
9.10 Exercises 267
PART IV • TOOLS FOR MAKING
STATISTICAL INFERENCES 271
Estimation Studies 271
Association Studies 271
Chapter 10 • Estimation Studies: 275
Inferring the Parameters of a Population from the
Statistics of a Sample
10.0 Learning Objectives 275
10.1 Motivation 275
10.2 Estimating the Occurrence of a Qualitative
Property for a Population 277
10.3 Estimating the Occurrence of a Quantitative
Property for a Population 283
10.4 Some Notes on Sampling 291
Selection Bias 291
Response Bias 292
10.5 SPSS Tutorial 292
10.6 Summary 293
10.7 Exercises 294
Chapter 11 • Chi-Square Analysis: 299
Investigating a Suspected Association Between
Two Qualitative Properties
11.0 Learning Objectives 299
11.1 Motivation 299
11.2 An Example 300
Establishing Whether a Relationship
Exists Between Two Properties 301
Determining Whethera Relationship
Suggested by a Sample Is Significant 303
11.3 An Extension: Testing the Statistical Significance
of Population Proportions 311
11.4-Summary 312
11.5 SPSS Tutorial 314
11.6 Exercises 325
Chapter 12 • The f-Test of Statistical Significance: 327
Comparing a Quantitative Property Assessed for
Two Different Groups
12.0 Learning Objectives 327
12.1 Motivation 328
12.2 An Example 328
12.3 Comparing Sample Means Using the Central
Limit Theorem (Optional) 330
12.4 Comparing Sample Means Using the f-Test 332
12.5 Summary 336
12.6 SPSS Tutorial 338
12.7 Exercises 364
Chapter 13 • Analysis of Variance: 347
Comparing a Quantitative Property Assessed for
Several Different Groups
13.0 Learning Objectives 347
13.1 Motivation 348
13.2 An Example 349
13.3 The F-Test 350
13.4 A Note on Sampling Distributions (Optional) 356
13.5 Summary 358
13.6 SPSS Tutorial 359
13.7 Exercises 364
Chapter 14 • Correlation Analysis and Linear Regression: 367
Assessing the Covariability of Two Quantitative Properties
14.0 Learning Objectives 367
14.1 Motivation 368
14.2 An Example 370
14.3 Visual Interpretation with a Scatter Plot (Optional) 371
14.4 Assessing an Association as a Covariance 373
14.5 Regression Analysis: Representing a Correlation as a Linear
Mathematical Model 379
14.6 Assessing the Explanatory Value of the Model 383
14.7 Summary 389
14.8 SPSS Tutorial 392
14.9 Exercises 404
Index 407
|
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| spelling | Bruhl, Robert H. Verfasser aut Understanding statistical analysis and modeling Robert Bruhl (University of Illinois at Chicago) Los Angeles ; London ; New Delhi ; Singapore ; Washington DC ; Mlebourne SAGE [2018] © 2018 xxiii, 411 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Statistische Analyse (DE-588)4116599-8 gnd rswk-swf SPSS (DE-588)4056588-9 gnd rswk-swf (DE-588)4123623-3 Lehrbuch gnd-content Statistische Analyse (DE-588)4116599-8 s DE-604 SPSS (DE-588)4056588-9 s Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029934842&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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| title | Understanding statistical analysis and modeling |
| title_auth | Understanding statistical analysis and modeling |
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| title_full | Understanding statistical analysis and modeling Robert Bruhl (University of Illinois at Chicago) |
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| title_full_unstemmed | Understanding statistical analysis and modeling Robert Bruhl (University of Illinois at Chicago) |
| title_short | Understanding statistical analysis and modeling |
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