Understanding Research Methods and Statistics An Integrated Introduction for Psychology

ISBN-10: 0618043047
ISBN-13: 9780618043040
Edition: 2nd 2001
Authors: Gary W. Heiman
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Description: This text successfully integrates statistics and research methods, by placing statistics in the context of research to help students grasp both topics more clearly. Discussions include all major descriptive and experimental methods, as well as  More...

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Book details

List price: $301.95
Edition: 2nd
Copyright year: 2001
Publisher: CENGAGE Learning
Publication date: 9/13/2000
Binding: Hardcover
Pages: 816
Size: 8.00" wide x 10.00" long x 1.25" tall
Weight: 3.630
Language: English

This text successfully integrates statistics and research methods, by placing statistics in the context of research to help students grasp both topics more clearly. Discussions include all major descriptive and experimental methods, as well as primary and secondary statistical procedures.

Note: Each chapter concludes with Putting It All Together, Chapter Summary, Key Terms, Review Questions, and Practice Problems
Introduction to Psychological Research
Introduction to the Scientific Method
Introduction (Or Why Am I Here?)
The Scientific Method
The Goals of Psychological Research Scientific Hypotheses
The Flaws in Scientific Research
The Logic of Designing and Interpreting Research
Beginning the Design: Asking the Question
Testing a Hypothesis by Discovering a Relationship
The Role of Statistical Procedures
Summary of the Flow of a Study Experimental Research Methods
Descriptive Research Methods
Understanding Reliability and Validity
Designing an Example Study
Critically Evaluating the Study
Understanding Reliability
Understanding Validity
Minimizing Threats to Validity and Reliability
Issues of Validity and Reliability in Descriptive Studies
Issues of Validity and Reliability in Experiments
Design Issues and Ethical Concerns in Experiments
Two Example Studies
Designing the Independent Variable
Designing the Dependent Variable
Controlling Extraneous Variables
Demand Characteristics
Research Involving Animals Research Ethics
Design Issues and Ethical Concerns in Descriptive Research
The Uses of Descriptive Research
Observational Studies
Field Surveys
Types of Sampling Techniques
Designing Interviews and Questionnaires
Ethical Issues in Descriptive Research
Descriptive Statistics
Summarizing Research
Using Frequency Distributions and Percentiles
More Statistical Notation
Types of Measurement Scales
Creating Simple Frequency Distributions
Types of Simple Frequency Distributions
Creating Relative Frequency Distributions
Types of Relative Frequency Distributions
Computing Percentile
A Word About Grouped Frequency Distributions
Summary of Formulas
Summarizing Research Using Measures of Central Tendency
More Statistical Notation
Understanding Central Tendency
The Mode
The Median
The Mean
Using the Mean in Research Summarizing
Research Using Central Tendency
Designing a Powerful Experiment
APA Format for Statistical Notation
Summary of Formulas
Summarizing Research Using Measures of Variability
More Statistical Notation
Understanding Variability
Describing the Sample Variance
Describing the Sample Standard Deviation
The Population Standard Deviation and the Population Variance
Variance as the Error in Predictions
Summarizing Research Using the Mean and Standard Deviation
APA Format for Statistical Notation
Summary of Formulas
Summarizing Research Using z-Scores
More Statistical Notation
Understanding z-Scores
Interpreting z-Scores: The z-Distribution
Using the z-Distribution to Compare
Different Distributions
Using the z-Distribution to Describe Individual Scores
Using z-Scores to Describe Sample Means
APA Format for Statistical Notation
Summary of Formulas
Correlational Research and Correlational Statistics
Correlational Research and the Correlation Coefficient
More Statistical Notation
Understanding Correlational Research
Distinguishing Characteristics of Correlational Analysis
Types of Relationships
Strength of the Relationship Using the Correlation Coefficient in Research
Computing the Correlation Coefficient
Creating a Powerful Correlational Design
Correlations in the Population
APA Format for Statistical Notation
Summary of Formulas
Using Linear Regression to Predict Scores
More Statistical Notation
Understanding Linear Regression
The Linear Regression Equation
Describing Errors in Prediction
When Using the Linear Regression Equation Predicting Variability: The Proportion of Variance Accounted
For A Word About Multiple Correlation and Regression
APA Format for Statistical Notation
Summary of Formulas
Introduction to Inferential Statistics
Probability and Making Decisions
About Chance Events More Statistical Notation
The Logic of Probability
Computing Probability
Obtaining Probability From the Standard Normal Curve
Making Decisions Based on Probability
Making Decisions About a Sample Mean
Summary of Formulas
Overview of Statistical Hypothesis
Testing: The z-Test
More Statistical Notation
The Role of Inferential Statistics in Research
Setting Up Inferential Procedures
Testing a Mean When sX is Known: The z-Test Interpreting zobt
Summary of Statistical Hypothesis
Testing The One-Tailed Test
Errors in Statistical Decision Making
APA Format for Statistical Notation
Summary of Formulas
The Single-Sample Study: Testing a Sample Mean or Correlation Coefficient
More Statistical Notation
Understanding the t-Test for a Single-Sample Mean
Calculating the Single-Sample t-Test
Estimating the Population m by Computing a Confidence Interval
Summary of the t-Test
Significance Tests for Correlation Coefficients
Summary of Testing a Correlation Coefficient
Maximizing the Power of the t-Test and Correlation Coefficient
APA Format for Statistical Notation
Summary of Formulas
Designing and Analyzing Two-Sample Experiments
The Two-Sample Between-Subjects Experiment and the Independent-Samples t-Test
More Statistical Notation
Designing the Two-Sample Experiment
Controlling Participant Variables in a Between-Subjects
Design The Independent-Samples t-Test
Describing the Relationship in a Two-Sample Experiment
Power and the Independent Samples t-Test
Eliminating Participants from the Data
APA Format for Statistical Notation
Summary of Formulas
The Two-Sample Within-Subjects Experiment and the Dependent-Samples t-Test
More Statistical Notation
Designs That Directly Control Participant Variables
Choosing a Design
The Dependent-Samples t-Test Power and the Dependent-Samples t-Test
APA Format for Statistical Notation
Summary of Formulas
Designing and Analyzing Complex Experiments
The One-Way Between-Subjects Experiment and the One-Way Analysis of Variance
More Statistical Notation
Designing Multilevel Experiments
Overview of ANOVA
Components of the F-Statistic
Computing the F-Ratio
Performing Post Hoc Comparisons
Summary of the Steps in Performing a One-Way ANOVA
Describing the Relationship in a One-Way ANOVA Power and the ANOVA
APA Format for Statistical Notation
Summary of Formulas
The Two-Way Between-Subjects Experiment and the Two-Way Analysis of Variance
More Statistical Notation
The Reason for Multifactor Studies
Overview of the Two-Way ANOVA
Computing the Two-Way ANOVA
Interpreting the Two-Way Experiment
Summary of the Steps in Performing a Two-Way ANOVA
APA Format for Statistical Notation
Summary of Formulas
Within-Subjects Experiments and Other Multifactor Designs
Controlling Participant Variables in Complex Designs
The One-Way Within-Subjects Analysis of Variance
The Two-Way Within-Subjects Design
The Two-Way Mixed Design
The Three-Way Design
The Test for Homogeneity of Variance: The Fmax Test
Other Ways to Compare the Means in a Factorial Design
Going Beyond the Analysis of Variance
APA Format for Statistical Notation
Summary of Formulas
Alternative Approaches to Design and Analysis
Quasi-Experiments and Single-Subject Designs
Understanding Quasi-Experiments
Quasi-Independent Variables
Involving Participant Variables
Quasi-Independent Variables
Involving Environmental Ev

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