5
1
9781483353005
Essential Statistics for the Behavioral Sciences / Edition 1 available in Paperback
Essential Statistics for the Behavioral Sciences / Edition 1
by Gregory J. Privitera
Gregory J. Privitera
- ISBN-10:
- 1483353001
- ISBN-13:
- 9781483353005
- Pub. Date:
- 01/08/2015
- Publisher:
- SAGE Publications
- ISBN-10:
- 1483353001
- ISBN-13:
- 9781483353005
- Pub. Date:
- 01/08/2015
- Publisher:
- SAGE Publications
Essential Statistics for the Behavioral Sciences / Edition 1
by Gregory J. Privitera
Gregory J. Privitera
$98.0
Current price is , Original price is $98.0. You
Buy New
$98.00Buy Used
$32.65
$98.00
-
SHIP THIS ITEM— This item is available online through Marketplace sellers.
-
PICK UP IN STORECheck Availability at Nearby Stores
Available within 2 business hours
This item is available online through Marketplace sellers.
$32.65
-
SHIP THIS ITEM
Temporarily Out of Stock Online
Please check back later for updated availability.
This item is available online through Marketplace sellers.
98.0
Out Of Stock
Overview
Employing the hallmark pedagogical support of his successful comprehensive text, award-winning author, teacher, and advisor Gregory J. Privitera offers a brief and engaging introduction to the field with Essential Statistics for the Behavioral Sciences. Practical examples, integrated SPSS® coverage and screenshots, and numerous learning tools make intimidating concepts accessible. Students will welcome Privitera's clear instruction, conversational voice, and application of statistics to current, real-life research problems.
Product Details
ISBN-13: | 9781483353005 |
---|---|
Publisher: | SAGE Publications |
Publication date: | 01/08/2015 |
Pages: | 576 |
Product dimensions: | 8.00(w) x 10.00(h) x (d) |
About the Author
Gregory J. Privitera is a professor of psychology at St. Bonaventure University where he is a recipient of its highest teaching honor, The Award for Professional Excellence in Teaching, and its highest honor for scholarship, The Award for Professional Excellence in Research and Publication. Dr. Privitera received his Ph D in behavioral neuroscience in the field of psychology at the State University of New York at Buffalo and continued with his postdoctoral research at Arizona State University. He is a nationally award-winning author and research scholar. His textbooks span across diverse topics in psychology and the behavioral sciences, including an introductory psychology text, four statistics texts, two research methods texts, and multiple other texts bridging knowledge creation across health, health care, and analytics. In addition, Dr. Privitera has authored more than three dozen peer-reviewed papers aimed at advancing our understanding of health and informing policy in health care. His research has earned recognition by the American Psychological Association, and in media to include Oprah’s Magazine, Time Magazine, and the Wall Street Journal. He mentors a variety of undergraduate research projects at St. Bonaventure University, where dozens of students, many of whom have gone on to earn graduate and doctoral degrees at various institutions, have coauthored and presented research work. In addition to his teaching, research, and advisement, Dr. Privitera is a veteran of the U.S. Marine Corps, is an identical twin, and is married with two daughters, Grace Ann and Charlotte Jane, and two sons, Aiden Andrew and Luca James.
Table of Contents
Part I: Introduction and Descriptive StatisticsChapter 1: Introduction to StatisticsThe Use of Statistics in ScienceDescriptive and Inferential StatisticsResearch Methods and StatisticsScales of MeasurementTypes of Variables for Which Data are MeasuredResearch in Focus: Evaluating Data and Scales of MeasurementSPSS in Focus: Entering and Defining VariablesChapter 2: Summarizing Data: Frequency Distributions in Tables and GraphsWhy Summarize Data?Frequency Distributions for Grouped DataIdentifying Percentile Points and Percentile RanksSPSS in Focus: Frequency Distributions for Quantitative DataFrequency Distributions for Ungrouped DataResearch in Focus: Summarizing Demographic InformationSPSS in Focus: Frequency Distribution for Categorical DataGraphing Distributions: Continuous DataGraphing Distributions: Discrete and Categorical DataResearch in Focus: Frequencies and PercentsSPSS in Focus: Histograms, Bar Charts, and Pie ChartsChapter 3: Summarizing Data: Central TendencyIntroduction to Central TendencyMeasures of Central TendencyCharacteristics of the MeanChoosing an Appropriate Measure of Central TendencyResearch in Focus: Describing Central TendencySPSS in Focus: Mean, Median, and ModeChapter 4: Summarizing Data: VariabilityMeasuring VariabilityRange and Interquartile RangeResearch in Focus: Reporting the RangeThe VarianceExplaining Variance for Populations and SamplesThe Computational Formula for VarianceThe Standard DeviationWhat Does the Standard Deviation Tell Us?Characteristics of the Standard DeviationSPSS in Focus: Range, Variance, and Standard DeviationPart II: Probability and the Foundations of Inferential StatisticsChapter 5: Probability, Normal Distribution, and z ScoresIntroduction to ProbabilityCalculating ProbabilityProbability and the Normal DistributionCharacteristics of the Normal DistributionResearch in Focus: The Statistical NormThe Standard Normal Distribution and z ScoresA Brief Introduction to the Unit Normal TableLocating ProportionsLocating ScoresSPSS in Focus: Converting Raw Scores to Standard z ScoresChapter 6: Characteristics of the Sample MeanSelecting Samples From PopulationsSelecting a Sample: Who’s In and Who’s Out?Sampling Distributions: The MeanThe Standard Error of the MeanFactors That Decrease Standard ErrorSPSS in Focus: Estimating the Standard Error of the MeanAPA in Focus: Reporting the Standard ErrorStandard Normal Transformations With Sampling DistributionsChapter 7: Hypothesis Testing: Significance, Effect Size, and PowerInferential Statistics and Hypothesis TestingFour Steps to Hypothesis TestingHypothesis Testing and Sampling DistributionsMaking a Decision: Types of ErrorTesting Significance: Examples Using the z TestResearch in Focus: Directional Versus Nondirectional TestsMeasuring the Size of an Effect: Cohen’s dEffect Size, Power, and Sample SizeAdditional Factors That Increase PowerSPSS in Focus: A Preview for Chapters 8 to 14APA in Focus: Reporting the Test Statistic and Effect SizePart III: Making Inferences About One or Two MeansChapter 8: Testing Means: One-Sample t Test With Confidence IntervalsGoing From z to tThe Degrees of FreedomReading the t TableComputing the One–Sample t TestEffect Size for the One-Sample t TestConfidence Intervals for the One-Sample t TestInferring Significance and Effect Size From a Confidence IntervalSPSS in Focus: One–Sample t Test and Confidence IntervalsAPA in Focus: Reporting the t Statistic and Confidence IntervalsChapter 9: Testing Means: Two-Independent-Sample t Test With Confidence IntervalsIntroduction to the Between-Subjects DesignSelecting Samples for Comparing Two GroupsVariability and Comparing Differences Between Two GroupsComputing the Two-Independent–Sample t TestEffect Size for the Two-Independent-Sample t TestConfidence Intervals for the Two-Independent-Sample t TestInferring Significance and Effect Size From a Confidence IntervalSPSS in Focus: Two-Independent–Sample t Test and Confidence IntervalsAPA in Focus: Reporting the t Statistic and Confidence IntervalsChapter 10: Testing Means: Related-Samples t Test With Confidence IntervalsRelated Samples DesignIntroduction to the Related-Samples t TestComputing the Related-Samples t TestMeasuring Effect Size for the Related-Samples t TestConfidence Intervals for the Related-Samples t TestInferring Significance and Effect Size From a Confidence IntervalSPSS in Focus: Related-Samples t Test and Confidence IntervalsAPA in Focus: Reporting the t Statistic and Confidence IntervalsPart IV: Making Inferences About The Variability of Two or More MeansChapter 11: One-Way Analysis of Variance: Between-Subjects and Within-Subjects (Repeated-Measures) DesignsAn Introduction to Analysis of VarianceThe Between-Subjects Design for Analysis of VarianceComputing the One-Way Between-Subjects ANOVAPost Hoc Tests: An Example Using Tukey’s HSDSPSS in Focus: The One-Way Between-Subjects ANOVAThe Within-Subjects Design for Analysis of VarianceComputing the One-Way Within-Subjects ANOVAPost Hoc Tests for the Within-Subjects DesignSPSS in Focus: The One-Way Within-Subjects ANOVAA Comparison of Within-Subjects and Between-Subjects Designs for ANOVA: Implications for PowerAPA in Focus: Reporting the Results of the One-Way ANOVAsChapter 12: Two-Way Analysis of Variance: Between-Subjects Factorial DesignIntroduction to Factorial DesignsStructure and Notation for the Two-Way ANOVADescribing Variability: Main Effects and InteractionsComputing the Two-Way Between-Subjects ANOVAAnalyzing Main Effects and InteractionsMeasuring Effect Size for Main Effects and the InteractionSPSS in Focus: The Two-Way Between-Subjects ANOVAAPA in Focus: Reporting the Results of the Two-Way ANOVAsPart V: Making Inferences About Patterns, Prediction, and Nonparametric TestsChapter 13: Correlation and Linear RegressionThe Structure of Data Used for Identifying Patterns and Making PredictionsFundamentals of the CorrelationThe Pearson Correlation CoefficientSPSS in Focus: Pearson Correlation CoefficientAssumptions and Limitations for Linear CorrelationsAlternatives to Pearson: Spearman, Point-Biserial, and PhiSPSS in Focus; Computing the Alternatives to PearsonFundamentals of Linear RegressionUsing the Method of Least Squares to Find the Regression LineUsing Analysis of Regression to Determine SignificanceSPSS in Focus: Analysis of RegressionA Look Ahead to Multiple RegressionAPA in Focus: Reporting Correlations and Linear RegressionChapter 14: Chi-Square Tests: Goodness-of-Fit and the Test for IndependenceDistinguishing Parametric and Nonparametric TestsThe Chi-Square Goodness-of-Fit TestSPSS in Focus: The Chi-Square Goodness-of-Fit TestInterpreting the Chi-Square Goodness-of-Fit TestThe Chi-Square Test for IndependenceMeasures of Effect Size for the Chi-Square Test for IndependenceSPSS in Focus: The Chi-Square Test for IndependenceAPA in Focus: Reporting the Chi-Square TestsAppendix A: Basic Math Review and Summation NotationAppendix B: Statistical TablesAppendix C: Chapter Solutions for Even-Numbered ProblemsFrom the B&N Reads Blog
Page 1 of