Essential Statistics for the Behavioral Sciences - International Student Edition

Gregory J. Privitera s Essential Statistics for the Behavioral Sciences offers a concise and pedagogically rich introduction to the field of behavioral science statistics. With unique features like chapter opening vignettes, SPSS integration, and ample application problems, Privitera creates unparalleled scaffolding for student learning.

Essentials of Statistics for the Behavioral Sciences is a concise version of Statistics for the Behavioral Sciences by award-winning teacher, author, and advisor Gregory J. Privitera.

The Second Edition provides balanced coverage for today s students, connecting the relevance of core concepts to daily life with new introductory vignettes for every chapter, while speaking to the reader as a researcher when covering statistical theory, computation, and application. Robust pedagogy allows students to continually check their comprehension and hone their skills while working through carefully developed problems and exercises that include current research and seamless integration of IBM® SPSS® Statistics.

Readers will welcome Privitera s thoughtful instruction, conversational voice, and application of statistics to real-world problems.

Autorentext

Gregory J. Privitera is a three-time national-award-winning author and 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 PhD 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. His texts span diverse topics in psychology and the behavioral sciences and include an introductory psychology text, three 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, health literacy, 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.

Klappentext

Gregory J. Privitera’s Essential Statistics for the Behavioral Sciences offers a concise and pedagogically rich introduction to the field of behavioral science statistics. With unique features like chapter opening vignettes, SPSS integration, and ample application problems, Privitera creates unparalleled scaffolding for student learning.

Zusammenfassung
Gregory J. Privitera's Essential Statistics for the Behavioral Sciences offers a concise and pedagogically rich introduction to the field of behavioral science statistics. With unique features like chapter opening vignettes, SPSS integration, and ample application problems, Privitera creates unparalleled scaffolding for student learning.

Inhalt
PART I: Introduction and Descriptive Statistics
Chapter 1:Introduction to Statistics
1.1 The Use of Statistics in Science
1.2 Descriptive and Inferential Statistics
MAKING SENSE-Populations and Samples
1.3 Research Methods and Statistics
MAKING SENSE-Experimental and Control Groups
1.4 Scales of Measurement
1.5 Types of Variables for Which Data Are Measured
1.6 Research in Focus: Evaluating Data and Scales of Measurement
1.7 SPSS in Focus: Entering and Defining Variables
Chapter 2: Summarizing Data: Frequency Distributions in Tables and Graphs
2.1 Why Summarize Data?
2.2 Frequency Distributions for Grouped Data
2.3 Identifying Percentile Points and Percentile Ranks
2.4 SPSS in Focus: Frequency Distributions for Quantitative Data
2.5 Frequency Distributions for Ungrouped Data
2.6 Research in Focus: Summarizing Demographic Information
2.7 SPSS in Focus: Frequency Distributions for Categorical Data
2.8 Graphing Distributions: Continuous Data
2.9 Graphing Distributions: Discrete and Categorical Data
MAKING SENSE- Deception Due to the Distortion of Data
2.10 Research in Focus: Frequencies and Percents
2.11 SPSS in Focus: Histograms, Bar Charts, and Pie Charts
Chapter 3: Summarizing Data: Central Tendency
3.1 Introduction to Central Tendency
3.2 Measures of Central Tendency
MAKING SENSE-Making the Grade
3.3 Characteristics of the Mean
3.4 Choosing an Appropriate Measure of Central Tendency
3.5 Research in Focus: Describing Central Tendency
3.6 SPSS in Focus: Mean, Median, and Mode
Chapter 4: Summarizing Data: Variability
4.1 Measuring Variability
4.2 The Range and Interquartile Range
4.3 Research in Focus: Reporting the Range
4.4 The Variance
4.5 Explaining Variance for Populations and Samples
4.6 The Computational Formula for Variance
4.7 The Standard Deviation
4.8 What Does the Standard Deviation Tell Us?
MAKING SENSE-Standard Deviation and Nonnormal Distributions
4.9 Characteristics of the Standard Deviation
4.10 SPSS in Focus: Range, Variance, and Standard Deviation
PART II: Probability and the Foundations of Inferential Statistics
Chapter 5: Probability, Normal Distributions, and z Scores
5.1 Introduction to Probability
5.2 Calculating Probability
5.3 Probability and the Normal Distribution
5.4 Characteristics of the Normal Distribution
5.5 Research in Focus: The Statistical Norm
5.6 The Standard Normal Distribution and z Scores
5.7 A Brief Introduction to the Unit Normal Table
5.8 Locating Proportions
5.9 Locating Scores
MAKING SENSE-Standard Deviation and the Normal Distribution
5.10 SPSS in Focus: Converting Raw Scores to Standard z Scores
Chapter 6: Characteristics of the Sample Mean
6.1 Selecting Samples From Populations
6.2 Selecting a Sample: Who's In and Who's Out?
6.3 Sampling Distributions: The Mean
6.4 The Standard Error of the Mean
6.5 Factors That Decrease Standard Error
6.6 SPSS in Focus: Estimating the Standard Error of the Mean
6.7 APA in Focus: Reporting the Standard Error
6.8 Standard Normal Transformations With Sampling Distributions
Chapter 7: Hypothesis Testing: Significance, Effect Size, and Power
7.1 Inferential Statistics and Hypothesis Testing
7.2 Four Steps to Hypothesis Testing
MAKING SENSE-Testing the Null Hypothesis
7.3 Hypothesis Testing and Sampling Distributions
7.4 Making a Decision: Types of Error
7.5 Testing for Significance: Examples Using the z Test
7.6 Research in Focus: Directional Versus Nondirectional Tests
7.7 Measuring the Size of an Effect: Cohen's d
7.8 Effect Size, Power, and Sample Size
7.9 Additional Factors That Increase Power
7.10 SPSS in Focus: A Preview for Chapters 8 to 14
7.11 APA in Focus: Reporting the Test Statistic and Effect Size
PART III: Making Inferences About One or Two Means
Chapter 8: Testing Means: One-Sample t Test With Confidence Intervals
8.1 Going From z to t
8.2 The Degrees of Freedom
8.3 Reading the t Table
8.4 Computing the One-Sample t Test
8.5 Effect Size for the One- Sample t Test
8.6 Confidence Intervals for the One-Sample t Test
8.7 Inferring Significance and Effect Size From a Confidence Interval …