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- Performance Psychology (Including I/O & Sport Psychology)
- Personality Theory: An Introduction
- Chapter 1: Introduction to Personality Theory & Development
- Chapter 10: Humanistic Theory
- Chapter 11: Cognitive Theory
- Chapter 12: Disorders, Applications & Trends
- Chapter 2: Personality Research & Assessment
- Chapter 3: Biological Components of Personality
- Chapter 4: Psychoanalytic Theory
- Chapter 5: Psychodynamic & Neo-Freudian Theories
- Chapter 6: Psychodynamic Assessment
- Chapter 7: Trait Theory
- Chapter 8: Learning Theory
- Chapter 9: Behavioral Theory Applications & Research
- Positive Psychology, Well-Being, and Resilience
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- Psychological Disorders
- Alphabetical Index of Disorders
- Attention Deficit Hyperactivity Disorder (ADHD)
- Dissociative Disorders
- Anxiety Disorders
- Eating Disorders
- Adjustment Disorders
- Impulse Control Disorders
- Mood Disorders
- Paraphilias
- Sleep Disorders
- Psychotic Disorders (including Schizophrenia)
- Sexual Disorders and Dysfunctions
- Somatoform Disorders
- Substance Related Disorders
- Personality Disorders
- Psychology 101
- Chapter 1: How to Learn Psychology
- Chapter 2: Biopsychology
- Chapter 3: Introduction to Development, Personality & Stage Theories
- Chapter 3.1: Motor & Cognitive Development
- Chapter 3.2: Erikson’s Stages of Psychosocial Development
- Chapter 3.3: Freud’s Stages of Psychosexual Development
- Chapter 3.4: Freud’s Structural & Topographical Model
- Chapter 3.5: Freud’s Ego Defense Mechanisms
- Chapter 3.6: Kohlberg’s Stages of Moral Development
- Chapter 4: Introduction to Learning Theory & Behavioral Psychology
- Chapter 5: Sensation & Perception
- Chapter 6: Section 1: Memory, Intelligence, and States of Mind
- Chapter 7: Motivation & Emotion
- Chapter 8: Social Psychology
- Chapter 9: Psychopathology
- Chapter 10: Psychotherapy
- References
- Psychology Article Archive
- Psychology Biographies
- Aaron Beck
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- Alfred Adler
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- Carl Jung
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- Edward Thorndike
- Emil Kraepelin
- Erik Erikson
- Hans Eysenck
- Harry Harlow
- Henry A. Murray
- Herman Ebbinghaus
- Ivan Pavlov
- Jean Piaget
- John Watson
- Max Wertheimer
- Sigmund Freud
- Wilhelm Wundt
- William James
- Psychology Bookshelf – Recommended Books
- Psychology Classroom
- Psychology Reference
- Psychotherapy Facts
- Relationships, Community, and Social Psychology
- Research Methods
- Chapter 1: Introduction to Research
- Chapter 1.10 Communicating Results
- Chapter 1.11 Replication
- Chapter 1.12 Putting it All Together
- Chapter 1.13 Chapter Conclusion
- Chapter 1.2 Determining a Theory
- Chapter 1.3 Defining Variables
- Chapter 1.4 Developing the Hypothesis
- Chapter 1.5 Standardization
- Chapter 1.6 Selecting Subjects
- Chapter 1.7 Testing Subjects
- Chapter 1.8 Analyzing Results
- Chapter 1.9 Determining Significance
- Chapter 10: Critical Analysis
- Chapter 2: The Research Report
- Chapter 3: Research Tools of the Trade
- Chapter 4: Single Subject Design
- Chapter 5: Experimental Design
- Chapter 6: Other Research Designs
- Chapter 7: Variables, Validity & Reliability
- Chapter 8: Descriptive Statistics
- Chapter 9: Inferential Statistics
- Chapter 1: Introduction to Research
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- State CE Requirements
- Statistics Primer (Revised)
- Unit 1: Measurement Scales, Data Tables, Graphing
- 02: Introduction: Goals of Statistics
- 03: Measurement Scales: Magnitude, Equal Intervals
- 04: Ratio, Interval, Ordinal, and Nominal Scales
- 05: Descriptive Statistics: Summarizing, Tabulating
- 06: Data Tables: Raw Data, Rank Ordered, Array
- 07: Raw Data Table: First Drawn, Least Useful
- 08: Ordered Array: Typically Highest to Lowest
- 09: Rank Ordered Table: Equal Scores + Rank Average
- 10: Percentile Rank: Scores That Fall at or Below
- 11: Frequency Distribution: Numerical Order
- 12: Grouped Frequency: Ranges Assigned to Dataset
- 13: Stem (Tens Digit) + Leaf Display (Ones Digit)
- 14: Graphing Data: Visually Inspect Results
- 15: Graph Qualities: Kurtosis and Skew
- 16: Leptokurtic Graph: High Peak with Small Range
- 17: Platykurtic Graph: Low Peak with Large Range
- 18: Mesokurtic Graph: Moderate Peak + Normal Range
- 19: Negative Skew: Extreme Scores on Left of Graph
- 20: Positive Skew: Extreme Scores on Right of Graph
- 21: Graphing Tricks 1: Show Statistics as Extreme
- 22: Graphing Tricks 2: Excluding Full Scores Range
- 23: Central Tendency: Mean, Median, Mode
- 24: Sample Distribution
- 25: Mean, Median, and Mode
- 26: Exercise 1: Complete Frequency Distribution
- 27: IQ Scores Graphed
- 28: Mean, Median, and Mode
- 29: Which Measure to Use? Mean, Median, Mode
- 30: Variability: Range, Variance, Standard Deviation
- 31: Range: Highest Minus Lowest
- 32: Interquartile Range: Percentile Ranks
- 33: Extrapolating: Distribution, Percentages
- 34: Extrapolating: Determining Percentiles
- 35: Extrapolating in Five Steps
- 36: Variance
- 37: Variance Chart: Raw Data, Distribution, Differences
- 38: Computing Variance: Original Data
- 39: Computing Standard Deviation
- 40: Measures: Range, Variance, Standard Deviation
- 41: Normal Curve (Bell-Shaped Curve)
- 42: Characteristics of a Perfect Normal Curve
- 43: Normal Distributions: Mean + Standard Deviation
- 44: Distribution of Intelligence
- 45: Eexercise 2: Construct, Graph, and Determine
- 46: Ordered Array
- 47: Frequency Distribution
- 48: Graph: Extreme Scores
- 49
- 50: Variance
- 51: Referral for Testing
- Unit 2: Correlations, Construct Measurement
- 02: Correlations- Relating or Varying Together
- 03: Correlation Coefficient Between Two Variables
- 04: Direction of Two Variables: Direct or Inverse
- 05: Perfect Correlation
- 06: Moderate and Zero
- 07: Correlation Coefficient Ranges
- 08: Coefficient of Determination
- 09: Misconceptions: Estimated Correlations
- 10: Misconceptions – Correlations
- 11: Cause and Effect: Direction of Two Variables
- 12: Pearson R or Product-Moment Correlation
- 13: Scatter Plot: Graphing Correlations
- 14: Pearson r Formula
- 15: Pearson r Chart: Data Chart
- 16: Computing r
- 17: Numerator (A)
- 18: Denominator (B)
- 19: Denominator (C)
- 20: ABC: Placing Results Back to Original Formula
- 21: Exercise 3: Graphing Data on Scatter Plot
- 22: Scatter Plot
- 23: Creating the Table
- 24: Computing r (A)
- 25: Computer r (B)
- 26: Computing r (C)
- 27: ABC
- 28: Coefficient of Determination
- 29: Measurement: Measure a Particular Phenomenon
- 30: Constructs: Variables That Can’t be Measured
- 31: Measuring a Construct: Observable Variables
- 32: Validity: Measuring What We Intend to Measure
- 33: Validity Types: Construct, Concurrent, Content
- 34: Construct Validity: Measurement Device
- 35: Concurrent Validity: Correlate or Vary
- 36: Discriminate Validity: Correlate or Vary
- 37: Predictive Validity: Predicting Scores
- 38: Content Validity: Generalized to Entire Content
- 39: Exercise 4: How to Determine
- 40: Reliability and Consistency
- 41: Reliability Defined
- 42: Standard Error of Measurement
- 43: Determining Reliability
- 44: Test-Retest Reliability
- 45: Parallel Forms Reliability
- 46: Split-Half and Odd-Even
- 47: Exercise 5: Assessing with Given Information
- 48: What To Do: Developing Math Ability Test
- 49: What To Do Next: Analyzing Test Results
- 50: Construct Validity: New Test vs. Known Test
- 51: Scatter Plot
- 52: Pearson r: Actual Correlational Coefficient
- 53: Cut Off Score: Mean and Standard Deviation
- Unit 3: Statistics Primer
- 02 – Standard Scores
- 03: The Normal Curve Revisited
- 04: Standard Deviation: Scores Distribution
- 05: Z-Scores: Another Look at Standard Deviation
- 06: Z-Score Conversions: Relying on Standard Deviation
- 07: T-Scores: Relying on Standard Deviation
- 08: College Entrance Exam Board (CEEB) Scores
- 09: Normal Curve Equivalent (NCE) Scores
- 10: Stanines or Standard Nine
- 11: Stanine Versus Z-Score
- 12: Wechsler and Deviation IQ
- 13: Otis-Lennon School Ability Test
- 14: Class Exercise: Calculating
- 15: Exercise Answers
- 16: Research: Descriptive + Inferential Statistics
- 17: Can We Trust the Results
- 18: Internal Validity: Subject Selection
- 19: Threats to Internal Validity
- 20: Threats to Internal Validity
- 21 – External Validity
- 22: Assuring Valid Results
- 23: The True Experiment: Rigid Research Methods
- 24: The Basic Experiment: Theory + Variables
- 25: The Basic Experiment: Constant, Hypothesis
- 26: The Basic Experiment: Test, Analyze, Report
- 27: Class Experiment
- 28 – Types of Research
- 29: Experimental Methods
- 30: Naturalistic Observation
- 31: Case Study: Studying Single Subject
- 32: Survey: Asking Specific Questions to Subjects
- 33: Correlational Studies: Determining Relationships
- 34: Testing: Gather Info and Compare Averages
- 35: Class Exercise: Simple Experiment
- Unit 4: Statistics Primer: Unit IV
- 02: Inferential Statistics
- 03: Terminology I: Population, Parameter, Sample
- 04: Terminology 2
- 05: Symbols I
- 06: Symbols 2
- 07: Symbols 3
- 08: Z-Test
- 09: Estimation: Point, Interval
- 10: Standard Error of the Mean
- 11: Computing the SE Mean
- 12 – Confidence Intervals
- 13: Two Statistic Levels: .95 or .99
- 14: Class Exercise
- 15: Computing the Mean
- 16: Computing the SD
- 17: Computing SE Mean
- 18: Population Parameter
- 19: z Test
- 20: z Score Conversions: Mean + Standard Deviation
- 21: z score SD
- 22 – Hypothesis Testing
- 23: Possible Hypotheses – Null and Alternative
- 24: Alpha and Beta
- 25: p-level
- 26 – Type I and Type II
- 27: Degrees of Freedom (df)
- 28 – t-Tests
- 29: Calculating t
- 30: Calculate t
- 31: Calculate t
- 32: Calculate t
- 33: t test – ABC
- 34: What does it mean?
- 35: Hypotheses -Null or Alternative
- 36 – Critical Values
- 37: Critical Values of r
- 38: Class Exercise: Achievement Scores Data
- 39: Sample Means: New Book vs Old Book
- 40: Hypotheses: Null, Alternative
- 41: Standard Deviation 1
- 42: Standard Deviation 2
- 43: t-Test
- 44: t-Test (B)
- 45: t-Test (C)
- 46: ABC
- 47: Critical Value
- Unit 5: ANOVA, Regression Analysis
- 02 – Analysis of Variance
- 03: ANOVA 2: One Way ANOVA
- 04: Factorial ANOVA 1
- 05: Factorial ANOVA 2: Main + Interaction Effects
- 06: ANOVA Data 1
- 07: ANOVA Data 2: 2 Way Variance Analysis, 2 means
- 08: ANOVA Data 3: 3 Way Variance Analysis, 3 means
- 09 – Regression Analysis
- 10: Regression Analysis 2
- 11: Regression Analysis 3
- 12: Sample Regression
- 13: Slope
- 14: Y Intercept
- 15: Prediction
- 16: Class Exercise – Predicting Outcome
- 17: Slope
- 18: Y Intercept
- 19: Prediction
- 20 – Factor Analysis
- 21 – Meta-Analysis
- 22 – Summary of Statistical Techniques
- 23: Central Tendency – Mean, Median, Mode
- 24: Assessing Variance 1 – Standard Deviation
- 25: Assessing Variance 2: Range, Interquartile Range
- 26: Assessing Relationships 1 – Pearson’s Correlation
- 27: Assessing Relationships 2 – Phi + Tetrachoric
- 28: Assessing Relationships- Multiple Correlation
- 29: Comparing Two Means
- 30: Three or more Means – One and Two Way ANOVAs
- 31: Advanced Statistics – Regression + Factor Analysis
- 32: Class Exercise I – Graphing Distribution
- 33: Class Exercise 2: Using Statistics
- 34: Exercise Answers 1- Mode +Interquartile Range
- 35: Exercise Answers 2
- 36: Exercise Answers 3 – Statistics for Scenarios
- Unit 1: Measurement Scales, Data Tables, Graphing
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