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Introduction to Research Methods: A Hands-On Approach 2nd ed. [Loose-leaf]

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  • Formāts: Loose-leaf, 376 pages, height x width x depth: 230x186x14 mm, weight: 539 g
  • Izdošanas datums: 09-Nov-2022
  • Izdevniecība: Sage Publications, Inc
  • ISBN-10: 1071879820
  • ISBN-13: 9781071879825
Citas grāmatas par šo tēmu:
Introduction to Research Methods: A Hands-On Approach 2nd ed.Palielināt
  • Formāts: Loose-leaf, 376 pages, height x width x depth: 230x186x14 mm, weight: 539 g
  • Izdošanas datums: 09-Nov-2022
  • Izdevniecība: Sage Publications, Inc
  • ISBN-10: 1071879820
  • ISBN-13: 9781071879825
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781071879825.html
Keywords:
The Second Edition of Bora Pajo’s Introduction to Research Methods: A Hands-on Approach makes research easy to understand and do by balancing quantitative with qualitative methods in clear and compelling prose. Updates include a new chapter on big data, a revamped chapter on qualitative designs, and citations in APA Style 7th Edition.

Also available as a digital option (courseware). Learn more about 9781071871256, Introduction to Research Methods: A Hands-on Approach - Vantage Digital Option, Second Edition.
Preface xvii
Acknowledgments xix
About the Author xxi
Chapter 1 The Purpose of Research
1(22)
Scientific Research and Its Purpose
2(2)
Theories of Knowledge
4(5)
Karl Popper's Falsifiability
4(2)
Thomas Kuhn's Structure of Scientific Revolution
6(3)
A Quick Look at Qualitative, Quantitative, and Mixed Methods
9(7)
Qualitative Research
9(1)
Research in Action 1.1 Illustration of a Qualitative Study
10(2)
Quantitative Research
12(1)
Research in Action 1.2 Illustration of a Quantitative Study
13(2)
Mixed Methods
15(1)
Ethical Research
16(4)
Ethical Rules
17(1)
Research Workshop 1.1 Complete a Course on Protecting Human Research Participants
18(1)
A Violation of Ethics
18(1)
Researchers' Biases
19(1)
Summary
20(1)
Key Terms
21(1)
Taking a Step Further
22(1)
Chapter 2 Formulating a Research Question
23(24)
Selecting Your Research Topic
24(4)
Fundamental vs. Applied Research
24(1)
Narrowing the Research Topic
25(2)
Research Workshop 2.1 An Example of Narrowing Down a Research Interest
27(1)
Operationalization of Constructs
28(5)
Ethical Consideration 2.1 Operationalizing Constructs
32(1)
Types of Variables
33(4)
Independent and Dependent Variables
33(1)
Control Variables
33(1)
Research Workshop 2.2 How to Identify Control Variables
34(1)
Confounding and Disturbance Variables
35(1)
Moderators and Mediators
36(1)
Types of Hypotheses
37(3)
Alternative Hypothesis and Null Hypothesis
37(1)
Research in Action 2.1 Illustration of Operationalization of Concepts
38(1)
Directional Hypothesis and Nondirectional Hypothesis
39(1)
Open-Ended Question
40(1)
Visualizing a Research Question
40(3)
Summary
43(1)
Key Terms
44(1)
Taking a Step Further
44(3)
Chapter 3 Researching and Writing the Literature Review
47(30)
Defining a Literature Review
48(1)
Exploring the Literature
49(6)
Using Libraries and Online Databases
50(2)
Using Search Engines
52(1)
Using Interlibrary Loan
53(1)
Writing Annotated Bibliographies
54(1)
Understanding and Organizing the Literature
55(12)
Creating a Guiding Table
55(1)
Research in Action 3.1 Illustration of Annotated Bibliographies
55(3)
Ethical Consideration 3.1 Research Funding
58(6)
Using the Conceptual Graph
64(1)
Organizing Your Work
64(1)
Conceptualizing Literature: Patterns
65(1)
Research in Action 3.2 Illustration of the Organization of Literature
65(2)
Thinking Critically
67(3)
Reading Critically
68(1)
Analyzing Studies
69(1)
Hypotheses or Research Questions
70(1)
Systematic Reviews of Literature
71(3)
Systematic Reviews vs. Narrative Literature Reviews
71(2)
Research Workshop 3.1 Writing the Literature Review
73(1)
Summary
74(1)
Key Terms
74(1)
Taking a Step Further
75(2)
Chapter 4 Quantitative Designs
77(24)
Categorizations of Research Studies
78(4)
Quantitative or Qualitative
79(1)
Exploratory Studies--Answering "What?"
80(1)
Descriptive Studies--Answering "How?"
80(1)
Explanatory Studies--Answering "Why?"
81(1)
Cross-Sectional vs. Longitudinal Studies
82(5)
Cross-Sectional Studies
82(1)
Research Workshop 4.1 The Advantages and Disadvantages of Cross-Sectional Designs
83(1)
Longitudinal Studies
84(1)
Ethical Consideration 4.1 Informed Consent During a Longitudinal Study
85(1)
Panel Studies
85(1)
Trend Studies
86(1)
Cohort Studies
86(1)
Causality in Research
87(3)
Nomothetic Research
87(2)
Idiographic Research
89(1)
Experimental Designs
90(9)
Classic Experimental Design
90(1)
Experimental and Control Groups
91(1)
Random Assignment
91(1)
Pre- and Posttesting
92(1)
Research in Action 4.1 Illustration of an Experimental Design
93(1)
Solomon Four-Group Experimental Design
94(1)
Quasi-Experimental Designs
95(1)
Randomized One-Group Posttest-Only Design
95(1)
Randomized Posttest-Only Control Group Design
95(1)
Nonrandom Posttest-Only Control Group Design
96(1)
Nonrandom Pretest-Posttest Control Group Design
96(1)
Nonrandom One-Group Pretest-Posttest Design
97(1)
Nonexperimental or Preexperimental Designs
98(1)
Nonrandom Cross-Sectional Survey Design
98(1)
Longitudinal Cohort Study
98(1)
Summary
99(1)
Key Terms
100(1)
Taking a Step Further
100(1)
Chapter 5 Measurement Errors, Reliability, and Validity
101(18)
Measurement Errors
102(4)
Defining Measurement Error
102(1)
Types of Measurement Errors
102(1)
Random Error
102(3)
Systematic Error
105(1)
Research Workshop 5.1 How to Minimize Measurement Error
106(1)
Reliability
106(4)
Interobserver or Interrater Reliability
107(1)
Test-Retest Reliability
108(1)
Internal Consistency Reliability
108(1)
Research in Action 5.1 Details on Strengthening a Questionnaire
109(1)
Validity
110(6)
Ethical Consideration 5.1 Selecting the Appropriate Instrument
111(1)
Face Validity
112(1)
Content Validity
112(1)
Construct Validity
112(1)
Criterion Validity, Concurrent Validity, and Predictive Validity
113(1)
Research Workshop 5.2 How to Select the Perfect Valid and Reliable Instrument for a Study
114(1)
Difference Between Reliability and Validity of the Measurement Instrument
115(1)
Summary
116(1)
Key Terms
117(1)
Taking a Step Further
117(2)
Chapter 6 Sampling
119(20)
Sampling
120(1)
Probability and Nonprobability Sampling
121(8)
Types of Nonprobability Sampling
123(1)
Convenience Sampling
123(2)
Snowball Sampling
125(1)
Ethical Consideration 6.1 Sampling
126(1)
Purposive Sampling
126(1)
Quota Sampling
127(2)
Research Workshop 6.1 Tips to Remember When Selecting Nonprobability Sampling
129(1)
Types of Probability Sampling
129(6)
Simple Random Sampling
130(1)
Systematic Random Sampling
131(1)
Stratified Random Sampling
131(2)
Research in Action 6.1 Two Studies Using Proportionate and Disproportionate Stratified Sampling
133(1)
Research Workshop 6.2 Tips to Remember When Selecting a Probability Sampling Method
134(1)
Cluster Random Sampling
135(1)
Sampling Assessment
135(2)
Sampling Error
136(1)
Confidence Interval
136(1)
Saturation
136(1)
Summary
137(1)
Key Terms
138(1)
Taking a Step Further
138(1)
Chapter 7 Data Collection for Quantitative Research
139(22)
Data Collection in Experimental Design
140(3)
Review of Experimental Design
110(31)
Collecting Data in Experimental Design
141(1)
Research Workshop 7.1 The Poverty-Related Simulation Experiment
142(1)
Ethical Consideration 7.1 Code of Research Ethics
143(1)
Data Collection in Quasi-Experimental Design
143(1)
Data Collection in Surveys
144(9)
Step 1 Develop a list of constructs
145(2)
Step 2 Determine constructs
147(1)
Step 3 Create the first variables
148(1)
Step 4 Turn constructs into variables
148(1)
Step 5 Craft the best-possible questions
149(2)
Step 6 Organize in a manner that attracts and holds participant attention
151(1)
Step 7 Create an answer scale
151(1)
Step 8 Conduct a pilot study to evaluate the instrument
152(1)
Methods of Data Collection
153(4)
Research in Action 7.1 The Use of Protocol to Ensure High Validity
153(1)
Personally Collecting Questionnaires
154(1)
Computer-Assisted Telephone Interviewing
155(1)
Research Workshop 7.2 Collecting Data
155(1)
Virtual Data Collection
156(1)
Research Workshop 7.3 Running Your Survey Online
157(1)
Summary
157(1)
Key Terms
158(1)
Taking a Step Further
159(2)
Chapter 8 Secondary Data
161(16)
Benefits of Using Secondary Data
162(4)
Availability of Data
162(1)
Availability of Design and Sampling Information
162(1)
Opportunities for Replication
163(1)
Protection of Participants
163(1)
Research in Action 8.1 Illustration of a Replication of a Previous Study
164(1)
Time-Effectiveness
165(1)
Cost-Effectiveness
165(1)
Large Data Sets
165(1)
Research Workshop 8.1 Scraping Data
166(1)
Major Sources of Secondary Data
166(6)
Government Statistics
166(1)
Research University Data
167(2)
Institutional Data
169(1)
Online Sources
169(2)
Research in Action 8.2 An Illustration of Available Data Sets
171(1)
Disadvantages of Secondary Data
172(3)
Uncertainty of Constructs
173(1)
Ambiguity of Measurement Error
173(1)
Passage of Time
174(1)
Ethical Consideration 8.1 Study Participants and Secondary Data
174(1)
Summary
175(1)
Key Terms
175(1)
Taking a Step Further
176(1)
Chapter 9 Entering and Organizing Quantitative Data
177(16)
The Purpose of Entering and Organizing Quantitative Data
177(1)
Preparing for Data Entry
178(6)
Logical Formatting
178(1)
Software Packages
179(3)
Research Workshop 9.1 Exploring Software Packages
182(1)
Unique Identification
183(1)
Ethical Consideration 9.1 Protecting the Anonymity of Participants
184(1)
Missing Data
184(1)
Organizing and Inputting Variables
184(6)
Coding and Codebooks
185(1)
Research in Action 9.1 Illustration of a Codebook
186(3)
Variable Names
189(1)
Variable Descriptions
189(1)
Notations for Responses
189(1)
Scales
190(1)
Summary
190(1)
Key Terms
191(1)
Taking a Step Further
191(2)
Chapter 10 Analyzing Quantitative Data
193(32)
Analyzing Quantitative Data
194(1)
Univariate Analysis
195(2)
Frequency Distributions
196(1)
Measures of Central Tendency
197(2)
Mean
198(1)
Median
198(1)
Mode
199(1)
Measures of Variability and Dispersion
199(4)
Ranges
200(2)
Variance and Standard Deviation
202(1)
Normal Distribution
203(2)
Skewness and Kurtosis
205(4)
Skewness
206(1)
Research in Action 10.1 Sample Size and Skewness
207(1)
Kurtosis
208(1)
Continuous and Discrete Variables
208(1)
Graphical Representation of Data
209(4)
Bar Graphs
209(1)
Histograms
210(1)
Line Graphs
211(1)
Ethical Consideration 10.1 Representation of Data
212(1)
Pie Charts
213(1)
Bivariate Analysis
213(9)
The Linear Model
214(2)
Correlation
216(2)
Causation
218(1)
Research Workshop 10.1 How to Find Correlation Using Excel, R, and IBM SPSS® Statistics
219(1)
Regression
220(1)
Scatterplots
221(1)
Summary
222(1)
Key Terms
223(1)
Taking a Step Further
223(2)
Chapter 11 Qualitative Designs and Data Collection
225(64)
Qualitative Research
226(1)
Research Design
227(6)
Ethnographic Designs
228(1)
Experimental Designs
228(1)
Research in Action 11.1 Illustration of Ethnographic Fieldwork
229(2)
Comparative Designs
231(1)
Process and Theory
231(1)
Differences in Setting and Design
232(1)
Data Collection
233(7)
Participant Observation
234(2)
Research Workshop 11.1 Participant Observation on the Subway
236(1)
Ethnographic Interviews
236(3)
Ethical Consideration 11.1 Is It Ethical?
239(1)
Variations to Consider
239(1)
Data Management
239(1)
Other Kinds of Qualitative Data
240(42)
Artifacts
240(1)
Images
241(2)
Videos
243(35)
Tables
278(2)
Research Workshop 13.1 Organization of Tables
280(1)
Figures
281(1)
Ethical Consideration 13.1 Misrepresenting Results
282(1)
Discussion
282(2)
Research in Action 13.3 Illustration of Organizing the Discussion
283(1)
Recommendations
284(2)
Research Workshop 13.2 Two Ways of Organizing the Discussion
285(1)
Summary
286(1)
Key Terms
286(1)
Taking a Step Further
287(2)
Chapter 14 Presenting Your Research
289(14)
Presenting Your Findings to an Audience
289(5)
Identifying the Main Points
291(1)
Ranking Your Topics
291(1)
Telling a Story
291(1)
Ethical Consideration 14.1 Accurate Presentations and Anonymity
292(1)
Literature, Hypotheses, Methodology, and Findings
293(1)
VisualAids
293(1)
Practical Tips
293(1)
Applying to Conferences
294(2)
Research Workshop 14.1 Applying to Conferences
295(1)
Publishing an Article
296(5)
Relevance of the Problem
298(1)
Writing Style
298(1)
Study's Design
298(1)
Quality of the Literature Review
299(1)
Research in Action 14.1 Illustration of a Presentation
299(2)
Sample Size
301(1)
Summary
301(1)
Taking a Step Further
302(1)
Chapter 15 Big Data
303(24)
Vastness of Data
304(6)
How Big Is Big Data?
304(1)
The Vs of Big Data
305(1)
Volume
305(1)
Velocity
306(1)
Variety
307(1)
Research in Action 15.1 Illustration of a Study Using Social Media Data
307(2)
Types of Big Data
309(1)
Structured
309(1)
Semistructured
309(1)
Unstructured
310(1)
Consuming Big Data
310(2)
Data Visualization
311(1)
The Purpose of Data Visualization
311(1)
Processing Big Data
312(3)
Machines That Learn
312(1)
Association
313(1)
Assimilation
313(1)
Equilibration
314(1)
Evolution of Machines
315(8)
Supervised Learning
316(1)
Semisupervised Learning
316(1)
Unsupervised Learning
317(1)
Reinforcement Learning
318(1)
Deep Learning
319(1)
Natural Language Processing
319(1)
Research Workshop 15.1 Playing With Google Trends
320(2)
Ethical Consideration 15.1 Machine Learning
322(1)
Summary
323(1)
Key Terms
324(1)
Taking a Step Further
325(2)
Glossary 327(12)
References 339(8)
Index 347