Data Analysis and Interpretation in the Behavioral Sciences

Name: Data Analysis and Interpretation in the Behavioral Sciences
Price: 39.37 USD
Availability: InStock
ISBN: 9780534529864

ISBN-10: 0534529860

ISBN-13: 9780534529864

Edition: 2003

Authors: Eugene B. Zechmeister, Emil J. Posavac

List price: $274.95

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Zechmeister and Posavac's unique, progressive pedagogical framework presents students with a model of analysis and interpretation called "I-D-E-A". This cutting edge model leads students through the processes of data inspection (I), description (D), estimating (E) confidence in their results, and announcing (A) their findings. Their friendly writing style and systematic approach to statistics involves the student in the topics presented. The authors stress the important first stage of data inspection and also demonstrate how both confidence intervals and effect sizes are complementary to traditional null hypothesis testing. Throughout the book, the authors emphasize the understanding and…

Book details

List price: $274.95
Copyright year: 2003
Publisher: Wadsworth
Publication date: 9/10/2002
Binding: Hardcover
Pages: 480
Size: 7.50" wide x 9.25" long x 1.00" tall
Weight: 2.288
Language: English

Emil J. Posavac (Ph.D., University of Illinois, Champaign) is Professor Emeritus of Psychology at Loyola University of Chicago where he served as director of the Applied Social Psychology Graduate Program and chairman of the Psychology Department. He has consulted with a number of public and private organizations. He has published over sixty papers and chapters, edited or co-edited six volumes on program evaluation and applied social psychology, and written numerous evaluation reports for health care and educational institutions. He has written a textbook (with Eugene B. Zechmeister) on statistical analysis based on emerging orientations that emphasize a more complete understanding and…



Preface to the Instructor


Preface to the Student



Introduction to the I-D-E-A Model of Data Analysis and Interpretation


Introduction


What Is/Are Data?


Why (Specifically) and How (Generally) Do Scientists Do Research?


What Is an Experiment?


How Are Behavior and Events Measured?


What Is the Role of Statistics in Behavioral Science Research?


How Do I Get a Sample of Behavior?


What Question Are You Asking?


How Confident Can I Be of My Answer?


An I-D-E-A for Data Analysis and Interpretation


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



Inspecting and Describing Data from One Group



Inspecting Data Point by Point


Introduction


Cleaning Data


How to Spot Suspicious Data Points


A Hypothetical Data Set


Using Tabular Inspection Methods


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



Inspecting Distributions of Data


Introduction


Using Histograms to Inspect Distributions


Frequency Polygons


Graphing Nominal Data


Transforming Data


What to Do About Skewed Distributions


Discarding Data


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



Describing Data From One Group


Introduction


How Do We Describe Data?


What Type of Data Are We Seeking to Describe?


Measures of Central Tendency


How Is Variability (Dispersion) Measured?


The Standard Deviation and Standard Scores


Data Description and the Normal Curve


How Do We Use a Normal Distribution to Describe the Relative Positions of Scores?


Comparing Apples and Oranges Again (or IQ and Height)


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



I-D-E-A for a Study Involving a Single Mean



Estimating Confidence in a Mean


Introduction


Point Estimates and Interval Estimates


What Is Sampling Variability?


The Sampling Distribution of the Mean


Probability and Normal Distributions


Probability and the Sampling Distribution of the Mean


How Do We Use a Sampling Distribution to Estimate Confidence in Our Finding?


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



Constructing a Confidence Interval and Announcing Results


Introduction


The t Distribution


Establishing a Confidence Interval for the Population Mean Based on the t Distribution


Interpreting Confidence Intervals


Increasing Precision and Confidence in Our Estimate


A Slight Variation When There Is a Hypothesized Population Mean


Announcing Results Based on a Single-Sample Mean


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



I-D-E-A When There Are Two Means



Inspecting and Describing Data From Two Groups


Introduction


Getting Two Sets of Data to Compare


Inspecting Two Distributions


Describing Two Distributions


Describing the Difference Between Two Samples


Repeated Measures Designs


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



Estimating Using Confidence Intervals


Introduction


Constructing Confidence Intervals for the Difference Between Two Means


What Makes Confidence Intervals Wide or Narrow?


Interpreting Differences Between Means


What Does the Magnitude of the Effect Size Mean?


Confidence Intervals for Difference Scores


Effect Sizes for Difference Scores


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



Estimating Using Null Hypothesis Significance Testing


Introduction


Testing Hypotheses


Rejection Criteria


The t Test for Independent Groups


Assumptions Underlying t Tests


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



Interpreting and Announcing Results


Introduction


Correctly Interpreting Null Hypothesis Significance Testing


Type I and Type II Errors


Pulling It All Together and Announcing Results


Presenting Exact Probabilities


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



I-D-E-A When There Are More Than Two Means



Inspecting, Describing, and Estimating Using Confidence Intervals


Introduction


Inspecting Data from an Independent Groups Design with One Independent Variable That Has Three or More Levels


Describing the Data: Measures of Central Tendency and Variability


Looking for Covariation


Constructing Confidence Intervals for an Independent Groups Experiment


Error Bars versus Confidence Intervals


Obtaining a Measure of Effect Size for an Independent Groups Experiment with One Independent Variable


Decisions About Differences Between Two Means in a Single-Factor Experiment


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



Estimating Confidence Using Null Hypothesis Significance Testing and Announcing Results


Introduction


The Role of NHST in an Independent Groups Experiment with One Independent Variable (the E in I-D-E-A)


The Logic of ANOVA


An Illustration of ANOVA: Does Type of Presentation Affect Recall?


Measures of Strength of Association for Independent Groups Designs


Two-Group Comparisons in a Multi-Group Experiment


Assessing Power in an Independent Groups Experiment


Announcing Results (the A in I-D-E-A)


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



I-D-E-A For Complex Designs


Introduction


Complex (Factorial) Designs


Inspecting Data from a Complex (Factorial) Design


Describing Results of a Complex Design: Cell Means, Main Effects, and Interaction


Constructing Confidence Intervals for Means in a Complex Design


Beyond 2 X 2


ANOVA for a Complex Design


Effect Size Measures for Complex Designs


Announcing Results of a Complex Design


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



I-D-E-A When Examining the Relationship Between Two Variables



Inspecting and Describing Correlational Data


Introduction


The Analysis Problem


Constructing Scatterplots


Describing Relationships Quantitatively


The Original Correlation Formula


Changing Scales


What We Have Done So Far


Inspecting the Relationships Between Two Variables


Limitations of Correlational Analyses


What Questions Do We Ask that Involve Two Variables?


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



Estimating Confidence Using Confidence Intervals


Introduction


Confidence Intervals for Correlation Coefficients


Interpreting Confidence Intervals of Correlation Coefficients


Effect Sizes of Correlation Coefficients


Interpreting the Effect Size of Correlations


Avoiding Common Misunderstandings of Correlations


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



Estimating Confidence Using Null Hypothesis Significance Testing and Announcing Results


Introduction


Null Hypotheses Involving Correlation Coefficients


Testing Whether r is Different from .00


Testing Whether r is Greater than .00


Using a Table Instead of the t Formula


Testing Whether r Differs from a Known [rho]


Testing Whether Two Independent Correlations Differ from Each Other


Pulling It All Together


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



Making Predictions


Introduction


Graphing Linear Equations


Graphing Variables Used in the Behavioral Sciences


Calculating a Regression Equation


Using Regression Predictions


An Important Additional Detail About the Precision of Predictions


Announcing the Results of a Regression Analysis


Cautions in Using Regression Equations to Make Predictions


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises



I-D-E-A for Studies with Nominal Data



I-D-E-A with Nominal Data


Introduction


What Question Are You Asking?


The I-D-E-A Model for a Proportion from a Single (Large) Sample


NHST with Nominal Data


Chi-square (x[superscript 2]) Goodness-of-Fit Test


Chi-square (x[superscript 2]) Test of Independence


Calculating an Effect Size for a Chi-Square Test of Independence


Announcing Results of a Chi-Square Test of Independence


What You Have Learned and the Next Step


Key Concepts


Answers to Your Turn Questions


Analyzing and Interpreting Data: Problems and Exercises


Appendix A



Proportions of Area Under the Standard Normal Curve



Critical Values of t



Critical Values of F



Transformation of r to Z[subscript r]



Critical Values of r



Critical Values of Chi-Square (x[superscript 2])



A Brief Introduction to Power Analysis


References


Index