- ホーム
- > 洋書
- > 英文書
- > Psychology
Full Description
An EasyGuide to Experimental Design and SPSS is a handbook that provides clear and concise guidance for research methods students faced with the many decisions involved in developing the most appropriate strategy to test a hypothesis. By presenting an integrated approach to the choice of design and statistical analysis this handbook helps students connect the choice of experimental design with the choice of an appropriate statistical test for data analyses. The EasyGuide also presents the exact steps to analyze data in SPSS, including ample screenshots. The authors provide a how-to for interpreting the output from SPSS analyses, and they help students format the relevant SPSS output into an APA-style results section.
Contents
Section 1Chapter 1: Marriage - 'Til Death Do Us PartWe Want to HelpBasic Steps of ResearchChapter 2: The Two Faces of CorrelationCorrelation as a Research DesignCorrelations as a StatisticChapter 3: Why Your Type fo Data Really Does Matter: Nominal, Ordinal, Interval, or RatioNominal DataOrdinal DataInterval DataRatio DataChapter 4: To KISS (Keep It Simply Student) or to Complicate Matters: Nominal DataHow Many Variables Should I Include?How Many Participants Should I IncludeHow Many Independent Variables ( IVs) Should I IncludeIncluding More Than One Independnt Variables (IV)Choosing the Number of Levels of Each VariableChoosing Your Dependent Variables (DVs)Avoiding the Un-Measurable Dependent Variables (DVs)How Many Dependent Variables (DVs) To IncludeSection II: Your Basic SPSS Tool BoxChapter 5: Why SPSS and Not Other Software, Your Calculator, Fingers, or ToesThe Structure of SPSSChapter 6: SPSS Data Hygiene: Columns, and Labels, and Values....Oh My.When to Create Your Data File: Yes Even Before Data CollectionSetting Up Your Data FileNaming and Labeling Your VariablesHow to Keep Track and Remember the Details of Your Data FileCreating New Variables in Your Data File: TransformationsConducting Analyses With Only Parts of Your Collected DataChapter 7: Tell Me About It: Descriptive StatisticsDescribing Nominal DataDescribing Ordinal DataDescribing Interval of Ratio DataDescribing Data with Two SamplesSection III: Designs, Statistics, Interpretaion, and Write-Up in APA StyleChapter 8: Celebrate Your Independence!: Between-Groups DesignsOne IV, Two LevelsBetween Groups with 2 Levels of an IVIndependent-Samples T-Test with a Pseudo-IVBetween Groups with More than 2 Levels of an IVChapter 9: Everybody Plays!: Repeated-Measures DesignsOne Independent Variable (IV) with Two-LevelsExpanding the Number of Levels for Your Independent VariableAdding Another Factor: Within-Subjects Factorial DesignsChapter 10: Complicating Matters: Advanced Research DesignsMixed Designs: One Between Variable and One Repeated-MeasuresA Multivariate Design: Measuring It All Including More Than One Dependent Variable In Your DesignANCOVAChapter 11: How do I know if That Relationship is Real? CorrelationsCorrelational Design: Two VariablesInterpreting Pearson's rAnalyzing Your DataPrediction with Two Variables: Simple Linear RegressionPrediction with Several Variables: Multiple Linear RegressionChapter 12: Statistics Charades: Two Variables, Two Categories.....is it a Chi Square?I Only Have One QuestionOne-way Chi Square With More Than Two LevelsNow I Only Have Two QuestionsSection IV: SummaryChapter 13: Mapping Your Decisions: You Can Get There From HereMaking Basic Decisions About Your DesignData with Distinct GroupsInterval or Ratio Data with Many LevelsChapter 14: Sample Results Sections for Each Type of DesignIndependent-Samples T-Test (True IV)Independent-Samples T-Test (Pseudo-IV)One-Way, Between-Groups ANOVA (True IV)Paired-Samples T-TestOne-Way, Within-Groups (Repeated-Measures) ANOVATwo-Way, Within-Groups (Repeated-Measures) ANOVAPearson's r CorrelationPearson's r Correlation and RegressionOne-Way ?2Two-Way ?2Chapter 15: Did I do that? Taking Advice From the ExpertsQuestions About Research DesignQuestions About Analyzing Your DataQuestions About Interpreting Your Data and Presenting Your ResultsWhen Interpreting Your Data
