Machine generated contents note: ch. 1 Thinking Like a Researcher -- Critical Thinking -- Thinking Critically About Ethics -- Ethics Codes -- Ethical Principles -- Ethical Standards -- Practice 1.1 Thinking Critically About Ethics -- The Scientific Approach -- The Scientific Approach and Decision Making -- The Scientific Approach and Knowledge -- The Scientific Method: Defined and Refined -- Overview of the Research Process (a.k.a. the Scientific Method) -- Step 1 Identify Your ToPIC -- Application 1.1 Step 1: Identify a Research ToPIC ---Focus on Academic Honesty -- Application 1.2 Step 1: Identify a Research ToPIC ---Focus on Technology Use -- Practice 1.2 Taking a Scientific Approach in Identifying a Research ToPIC -- Step 2 Find, Read, and Evaluate Past Research -- Step 3 Further Refine Your ToPIC and Develop a Hypothesis or Research Question -- Step 4 Choose a Research Design -- Step 5 Plan and Carry Out Your Study --

Contents note continued: Practice 1.3 Identifying Different Types of Research Designs -- Step 6 Analyze Your Data -- Step 7 Communicate Results -- Practice 1.4 Identifying and Avoiding Plagiarism -- Proof and Progress in Science -- Application 1.3 The Scientific Method: Plagiarism Study Example -- Chapter Resources -- Key Terms -- Do You Understand the Chapter? -- ch. 2 Build a Solid Foundation for Your Study by Finding, Reading, and Evaluating Past Research -- Types of Sources -- Primary Versus Secondary Sources -- Scholarly Versus Popular Sources -- Types of Scholarly Works -- Articles in Academic Journals -- Other Types of Scholarly Work -- Practice 2.1 Article Comparison -- Strategies to Identify and Find Past Research -- Searching Library Databases by ToPIC -- More Search Strategies -- Application 2.1 Database Search for Cell Phone ToPIC -- Find the Full Text of a Source -- Practice 2.2 Find Research on Your ToPIC -- Reading and Evaluating Primary Research Articles --

Contents note continued: Format of Unpublished Manuscripts Versus Published Research Articles -- Organization of Primary Research Articles -- Application 2.2 Titles of Two Articles About Disruptive Cell Phones -- Application 2.3 Abstracts -- Review of Key Concepts: Discerning a Study's Design From the Abstract -- Application 2.4 Compare Introductions of End et al. (2010) and Nordstrom et al. (2009) -- Shape of a Primary Research Article -- Develop Study Ideas Based on Past Research -- Application 2.5 Replicate Study With a Different Sample, Setting, or Measure -- Application 2.6 Conduct an Experiment Based on a Quasi- or Non-Experimental Study -- Application 2.7 Conduct a Similar Study With a Different Outcome or Dependent Variable -- Application 2.8 Examine How Another Variable Impacts Results -- APA Format for References -- Practice 2.3 Write a Reference Using APA Format -- Practice 2.4 Read, Evaluate, and Reference a Primary Research Article on Your ToPIC --

Contents note continued: Chapter Resources -- Key Terms -- Do You Understand the Chapter? -- ch. 3 The Cornerstones of Good Research: Reliability and Validity -- Reliability and Validity Broadly Defined -- Reliability and Validity at the Study Level -- Study Reliability -- Internal Validity -- Review of Key Concepts: Independent and Dependent Variables -- External Validity -- Practice 3.1 Distinguishing Between External Validity, Internal Validity, and Reliability at the Study Level -- Balancing Internal and External Validity -- Application 3.1 Balancing Internal and External Validity in Cell Phone Research -- Practice 3.2 Assessing the Balance of Internal and External Validity in a Study From Your ToPIC -- Reliability and Validity of Measurement -- Constructs and Operational Definitions -- Deciding How to Measure Your Constructs -- Scales of Measurement -- Practice 3.3 Identifying Scales of Measurement -- Types of Measures -- Questionnaires --

Contents note continued: Observational and Unobtrusive Measures -- Assessing Reliability and Validity of Your Measure -- Assessing Reliability -- Assessing Validity -- Practice 3.4 Your Research ToPIC and Reliability and Validity -- Using Data Analysis Programs -- Entering Data -- Computing Scale Scores -- Computing Internal Consistency -- Practice 3.5 Examples From the Literature -- Chapter Resources -- Key Terms -- Do You Understand the Chapter? -- Practice Dataset -- ch. 4 Designing a Descriptive Study -- When Is a Descriptive Study Appropriate? -- Understand Prevalence and Trends -- Explore a Phenomenon in Depth -- Examine a Phenomenon in a Different Population -- Review of Key Concepts: External Validity -- Practice 4.1 Identify a Descriptive Study Based on Your ToPIC -- Methods for Descriptive Studies -- Survey Research -- Observational Research -- Review of Key Concepts: Scales of Measurement -- Archival Research --

Contents note continued: Practice 4.2 Evaluate Methods for a Descriptive Study on Your ToPIC -- Validity in Descriptive Studies -- Review of Key Concepts: Measurement Validity, Internal Validity, and External Validity -- Defining the Population and Obtaining a Sample -- Who or What Is the Population of Interest? -- How Will You Obtain a Sample From Your Population? -- Application 4.1 Examples of Probability Sampling -- Application 4.2 Examples of Nonprobability Sampling -- Beyond Description -- Practice 4.3 Define the Population and Decide How to Collect a Sample for Your Study -- Chapter Resources -- Key Terms -- Do You Understand the Chapter? -- ch. 5 Describing Your Sample -- Ethical Issues in Describing Your Sample -- Practical Issues in Describing Your Sample -- Review of Key Concepts: Qualitative and Quantitative Measures -- Qualitative Analysis -- Analytic Induction -- Thematic Analysis -- A Priori Content Analysis --

Contents note continued: Practice 5.1 Using Thematic Analysis and A Priori Content Analysis -- Descriptive Statistics -- Describe How Often a Score Appears in the Sample -- Practice 5.2 Describe How Often Scores Appear in the Sample -- Describe the Central Tendency -- Practice 5.3 Calculate the Central Tendency -- Describe the Variability of Scores in the Sample -- Practice 5.4 Calculating Variability -- Choosing the Appropriate Descriptive Statistics -- Review of Key Concepts: Scales of Measurement -- Describing Variables Measured on a Nominal Scale -- Describing Variables Measured on an Ordinal Scale -- Describing Variables Measured on Interval and Ratio Scales -- Using Data Analysis Programs for Descriptive Statistics -- Calculating Frequencies With a Data Analysis Program -- Calculating Central Tendency and Variability With a Data Analysis Program -- Reporting Results in a Research Report --

Contents note continued: Practice 5.5 Identifying the Type of Distribution and Choosing the Appropriate Descriptive Statistics -- Comparing Interval/Ratio Scores With z Scores and Percentiles -- Z Scores -- Percentiles -- Example z Score and Percentile Calculation -- Practice 5.6 Calculating a z Score and Percentile -- Using Data Analysis Programs for z Scores and Percentiles -- The Big PIC ture -- Application 5.1 Example From the Research Literature -- Chapter Resources -- Key Terms -- Do You Understand the Chapter? -- Practice Dataset and Analyses -- ch. 6 Beyond Descriptives: Making Inferences Based on Your Sample -- Inferential Statistics -- Inferential Versus Descriptive Statistics -- Review of Key Concepts: Population and Sample -- Probability Theory -- Sampling Distribution Versus Frequency Distribution -- Application 6.1 Example of Hypothesis Testing -- Hypothesis Testing -- Null and Alternative Hypotheses -- Rejecting the Null Hypothesis --

Contents note continued: Practice 6.1 Null and Alternative Hypotheses -- Review of Key Concepts: The Normal Distribution -- Testing a One-Tailed Versus a Two-Tailed Hypothesis -- Setting the Criterion Level (p) -- Practice 6.2 One-Tailed and Two-Tailed Hypotheses -- Errors in Hypothesis Testing -- Type I and Type II Errors -- Application 6.2 Applying the Complete Hypothesis Testing Process in a Study -- Reducing the Chance of a Type I Error -- Practice 6.3 Understanding the Hypothesis Testing Process -- Reducing the Chance of a Type II Error -- Practice 6.4 Interpreting Results -- Effect Size and Practical Significance -- Application 6.3 Determining the Effect Size and Practical Significance in a Study -- Review of Key Concepts: z Scores -- Comparing Your Sample to a Known or Expected Score -- Null Hypothesis (H0) -- Alternative Hypothesis (Ha) -- Calculating a One-Sample t Test -- Practice 6.5 Determining Whether a t-Test Result Is Significant --

Contents note continued: Using Data Analysis Programs to Compute the One-Sample t Test -- Application 6.4 Sample Results and Discussion Sections Following APA Format -- Practice 6.6 Writing Results and Discussion Sections -- Chapter Resources -- Key Terms -- Do You Understand the Chapter? -- Practice With Statistics -- Practice With SPSS -- ch. 7 Examining Relationships Among Your Variables: Correlational Design -- Correlational Design -- Rationale for Correlational Designs -- Limitations of Correlational Designs -- Designing Powerful Correlational Designs -- Review of Key Concepts: Scales of Measurement -- Basic Statistics to Evaluate Correlational Research -- Relationship Between Two Interval or Ratio Variables -- Practice 7.1 Types of Relationships -- Review of Key Concepts: Hypothesis Testing -- Relationship Between a Dichotomous Variable and an Interval/Ratio Variable -- Application 7.1 A Study Examining the Relationship Between Texting and Literacy --

Contents note continued: Practice 7.2 Evaluating Correlations -- Application 7.2 An Example of the Use of Point-Biserial Correlation -- Regression -- Linear Regression -- Multiple Regression -- Practice 7.3 Practice With Regression Equations -- Application 7.3 Example of Multiple Regression -- Using Data Analysis Programs -- Data Entry -- Interpreting Output -- Application 7.4 Sample Results and Discussion for Correlation and Regression -- Point-Biserial Correlation Coefficient -- Chapter Resources -- Key Terms -- Do You Understand the Chapter? -- Practice With Statistics -- Practice With SPSS -- ch. 8 Examining Causal Relationships Among Your Variables: Introduction to Experimental Design -- Testing Cause and Effect -- Requirements for Causality -- Review of Key Concepts: Validity -- Practice 8.1 Testing Cause and Effect -- Threats to Internal Validity -- Why the One-Group Pretest--Posttest Design Does Not Demonstrate Causality -- Group Designs --

Contents note continued: Practice 8.2 Identifying Threats to Internal Validity -- How an Experiment Can Demonstrate Causality -- Review of Key Concepts: Components of an Experiment -- Practice 8.3 Design an Experiment -- Basic Issues in Designing an Experiment -- Review of Key Concepts: Power -- Recruiting Participants -- Random Assignment -- Controlling Other Extraneous Variables and Confounds -- IV Manipulation -- Practice 8.4 Distinguishing Between Variables That Can and Cannot Be Manipulated -- DV Measures -- Review of Key Concepts: Sensitivity, and Floor and Ceiling Effects -- Practice 8.5 Find and Evaluate an Experiment on Your ToPIC -- Application 8.1 Research Examining Mobile Devices and Pedestrian Safety -- Other Threats to Internal Validity -- Demand Characteristics -- Experimenter Expectancy Effects -- Diffusion of Treatment -- Balancing Internal and External Validity -- Limits of Experimental Design --

Contents note continued: Application 8.2 Example and Rationale of a Quasi-Experiment on the ToPIC of Academic Honesty -- Chapter Resources -- Key Terms -- Do You Understand the Chapter? -- ch. 9 Independent-Groups Designs -- Designs With Two Independent Groups -- Correlational Designs -- Quasi-Experiments -- Review of Key Concepts: Three Requirements for an Experiment -- Simple Experiments -- Designing a Simple Experiment -- Review of Key Concepts: Designing an Experiment -- Independent-Samples t Tests -- Practice 9.1 Simple Experiment Design Practice -- Review of Key Concepts: Type I and Type II Errors -- Practice 9.2 Type I and Type II Errors -- Confidence Intervals -- Review of Key Concepts: Strength of the Effect -- Effect Size -- Practical Significance -- Using SPSS to Analyze Data From a Two Independent-Groups Design -- Data Entry -- Data Analysis -- Application 9.1 Sample Results and Discussion for a Simple Experiment Using Independent Groups --

Contents note continued: Designs With More Than Two Independent Groups -- Practice 9.3 Practice Interpreting a Two-Group Design -- Advantages of the Multiple Independent-Groups Design -- One-Way Analysis of Variance -- Review of Key Concepts: Within- and Between-Groups Variance -- Practice 9.4 Practice Completing and Interpreting a Summary Table -- Using SPSS to Analyze the Results From a Multiple-Groups Experiment -- Application 9.2 Sample Write-Up (of Hypothetical Results and Discussion) Using APA Format -- Practice 9.5 Practice With the Analysis and Interpretation of a Multiple-Groups Study -- Overview -- Chapter Resources -- Key Terms -- Do You Understand the Chapter? -- Practice With Statistics -- Practice With SPSS -- ch. 10 Dependent-Groups Designs -- Review of Key Concepts: Types of Independent-Groups Designs -- Dependent-Groups Designs -- Matched-Pairs Design -- Repeated Measures Design -- Practice 10.1 Considering Dependent Designs --

Contents note continued: Review of Key Concepts: Assumptions of the Independent-Samples t Test -- Analysis of Dependent Two-Group Designs -- Using SPSS to Analyze the Results of Simple Dependent-Groups Designs -- Application 10.1 Sample Results and Discussion for a Hypothetical Experiment Using Two Dependent Groups -- Practice 10.2 Practice With a Dependent Design -- Designs With More Than Two Dependent Groups -- Practice 10.3 Practice With Participant Assignment in Dependent Designs -- Analysis of Dependent Multiple-Groups Designs -- Review of Key Concepts: ANOVA -- Practice 10.4 Practice Interpreting a Summary Table for a Dependent-Samples ANOVA -- Application 10.2 Sample Results and Discussion for a Hypothetical Experiment Using a Multiple Dependent-Groups Design -- Practice 10.5 Practice Interpreting a Dependent-Samples ANOVA -- Chapter Resources -- Key Terms -- Do You Understand the Chapter? -- Practice With Design and Statistics -- Practice With SPSS --

Contents note continued: ch. 11 Factorial Designs -- Basic Concepts in Factorial Design -- Types of Factorial Designs -- Factorial Notation -- Practice 11.1 Identify Types of Factorial Designs -- Main Effects and Interaction Effects -- Rationale for Factorial Designs -- Investigate Complex Relationships -- Systematically Examine Extraneous Variables and Confounds -- Review of Key Concepts: Heterogeneity and Control -- Application 11.1 Building on Past Research by Designing a Factorial -- 2 [×] 2 Designs -- Main Effects in a 2 [×] 2 Design -- 2 [×] 2 Tables and Graphs -- Practice 11.2 Graph a 2 [×] 2 Interaction -- Interaction Hypotheses -- Practice 11.3 Develop an Interaction Hypothesis for Your ToPIC -- Analyzing 2 [×] 2 Designs -- Analyzing a 2 [×] 2 Independent-Groups Design -- Review of Key Concepts: Independent-Groups Design -- Calculate the Sum of Squares -- Calculate the Degrees of Freedom -- Calculate the Mean Squares --

Contents note continued: Calculate the F Ratios -- Effect Size -- Practice 11.4 Complete a Two-Way Between-Subjects ANOVA Summary Table -- Post Hoc Analyses -- Using Data Analysis Programs to Calculate a Two-Way ANOVA -- Reporting and Interpreting Results of a Two-Way ANOVA -- Results Section -- Interpreting Results in the Discussion Section -- Application 11.2 Sample Results for a Two-Way Between-Subjects ANOVA -- Practice 11.5 Write a Results Section and Consider the Practical Significance of the Results -- Dependent-Groups and Mixed Factorial Designs -- Review of Key Concepts: Dependent-Groups Design -- Using a Data Analysis Program to Analyze Dependent-Groups Factorial Designs -- Using a Data Analysis Program to Analyze Mixed Designs -- The Big PIC ture -- Chapter Resources -- Key Terms -- Do You Understand the Chapter? -- Practice With Datasets and Analyses -- ch. 12 Nonparametric Statistics -- Parametric Versus Nonparametric Statistics --

Contents note continued: Review of Key Concepts: Assumptions of Parametric Statistics -- Nonparametric Tests for Nominal Data -- Independent-Groups Designs With Nominal Outcome Measures -- Application 12.1 Sample Write-Up of the Results of the Example Study Using Chi-Square -- Dependent-Groups Designs With Nominal Outcome Measures -- Practice 12.1 Practice With Different Types of Chi-Square -- Nonparametric Statistics for Ordinal (Ranked) Data -- Practice 12.2 Identifying Appropriate Statistics for Nominal Data -- Spearman's Rho -- Two-Group Designs -- Multiple-Group Designs -- Practice 12.3 Identifying Appropriate Statistics for Ordinal Data -- Summary -- Chapter Resources -- Key Terms -- Do You Understand the Chapter? -- Practice With Statistics -- Practice With SPSS -- ch. 13 Focusing on the Individual: Case Studies and Single N Designs -- Samples Versus Individuals -- Review of Key Concepts: Goals of Descriptive, Correlational, and Experimental Studies --

Contents note continued: Review of Key Concepts: Type I and Type II Errors -- The Case Study -- Conducting a Case Study -- Application 13.1 Two Examples of Embedded Case Studies From the Literature on Academic Honesty -- Strengths and Limitations of the Case Study -- Single N Designs -- Conducting a Single N Study -- Stability of the Baseline -- More Advanced Single N Designs -- Strengths and Limitations of Single N Designs -- Practice 13.1 Single N Designs -- Choosing Between a Sample, Case Study, or Single N Design -- Chapter Resources -- Key Terms -- Do You Understand the Chapter? -- ch. 14 How to Decide? Choosing a Research Design and Selecting the Correct Analysis -- First and Throughout: Base Your Study on Past Research -- Choosing a Research Design -- Descriptive, Correlational, Quasi-Experimental, or Experimental Design? -- Practice 14.1 Choosing a Research Design -- Additional Decisions for Correlational Designs, Quasi-Experiments, and Experiments --

Contents note continued: Practice 14.2 Deciding Between the Independent- and Dependent-Groups Designs -- Selecting Your Statistical Analyses -- Practice 14.3 Selecting Appropriate Statistical Analyses -- Application 14.1 Two Examples From the Research Literature -- The Big PIC ture -- Chapter Resources -- Do You Understand the Chapter? -- Appendix A Answers to Practice Questions -- Appendix B APA Style and Format Guidelines -- Writing an APA-Style Research Report -- Steps in Writing a Research Proposal and Report -- 10 Common Mistakes and How to Fix Them -- APA Format for Citations Within Your Paper -- APA Format for References -- Example of an APA-Style Manuscript -- Example of a Published Article -- Appendix C Statistical Tables -- C.1.Table of Random Numbers -- C.2.Estimated Sample Size Needed Based on Population Size, Confidence Level, and Confidence Interval -- C.3.Percentage of Area Under the Normal Curve Between the Mean and a z Score --

Contents note continued: C.4.Critical t Values for a Particular Probability Level and df -- C.5.Critical Values for Pearson's Correlation Coefficient (r) -- C.6.Critical F Values for ANOVA With a Particular Probability Level and df -- C.7.Critical Values for Chi-Square (Χ2) -- C.8.Critical Values for Spearman's Rho (rs) -- Appendix D Statistical Formulas -- D.1.Computational Formula for Standard Deviation -- D.2.Calculating a Skewness Statistic -- D.3.Computational Formula for One-Sample t Test -- D.4.Computational Formula for Pearson's r -- D.5.Computational Formula for Independent-Samples t Test -- D.6.Computational Formulas for Sum of Squares (SS) for One-Way Independent-Samples ANOVA -- D.7.Computational Formula for Tukey's HSD Post Hoc Test -- D.8.Computational Formulas for Sum of Squares (SS) for Dependent-Samples ANOVA -- D.9.Computational Formulas for Sum of Squares (SS) for a Two-Way ANOVA -- D.10.Computational Formula for McNemar's Test --

Contents note continued: D.11.Computational Formula for Cochran Q Test -- D.12.Computational Formula for Spearman's Rho Tied Ranks -- D.13.Computational Formula for Mann-Whitney U Test -- D.14.Computational Formula for Rank Sums Test -- D.15.Computational Formula for Wilcoxon T Test -- D.16.Computational Formula for Kruskal-Wallis T Test -- D.17.Computational Formula for Friedman Χ2 Test.