External
An Introduction to Psychological Statistics
We are constantly bombarded by information, and finding a way to filter that information in an objective way is crucial to surviving this onslaught with your sanity intact. This is what statistics, and logic we use in it, enables us to do. Through the lens of statistics, we learn to find the signal hidden in the noise when it is there and to know when an apparent trend or pattern is really just randomness.
- Author
- Foster et al.
- Publisher
- LibreTexts
- Source
- LibreTexts
- License
- CC BY-NC-SA
- Language
- EN
- Category
- Basic Sciences
Contents· 106 sections
- 01: Introduction
- 1.01: What are statistics
- 1.02: Why do we study statistics
- 1.03: Types of Data and How to Collect Them
- 1.04: Collecting Data
- 1.05: Type of Research Designs
- 1.06: Types of Statistical Analyses
- 1.07: Mathematical Notation
- 1.08: Exercises
- 02: Describing Data using Distributions and Graphs
- 2.01: Graphing Qualitative Variables
- 2.02: Graphing Quantitative Variables
- 2.03: Exercises
- 03: Measures of Central Tendency and Spread
- 3.01: What is Central Tendency
- 3.02: Measures of Central Tendency
- 3.03: Spread and Variability
- 3.04: Exercises
- 04: z-scores and the Standard Normal Distribution
- 4.01: Normal Distributions
- 4.02: Z-scores
- 4.03: Z-scores and the Area under the Curve
- 4.04: Exercises
- 05: Probability
- 5.01: What is probability
- 5.02: Probability in Graphs and Distributions
- 5.03: The Bigger Picture
- 5.04: Exercises
- 06: Sampling Distributions
- 6.01: People Samples and Populations
- 6.02: The Sampling Distribution of Sample Means
- 6.03: Using Standard Error for Probability
- 6.04: Sampling Distribution Probability and Inference
- 6.05: Exercises
- 07: Introduction to Hypothesis Testing
- 7.01: Logic and Purpose of Hypothesis Testing
- 7.02: The Probability Value
- 7.03: The Null Hypothesis
- 7.04: The Alternative Hypothesis
- 7.05: Critical values p-values and significance level
- 7.06: Steps of the Hypothesis Testing Process
- 7.07: Movie Popcorn
- 7.08: Effect Size
- 7.09: Office Temperature
- 7.10: Different Significance Level
- 7.11: Other Considerations in Hypothesis Testing
- 7.E: Introduction to Hypothesis Testing (Exercises)
- 08: Introduction to t-tests
- 8.01: The t-statistic
- 8.02: Hypothesis Testing with t
- 8.03: Confidence Intervals
- 8.04: Exercises
- 09: Repeated Measures
- 9.01: Change and Differences
- 9.02: Hypotheses of Change and Differences
- 9.03: Increasing Satisfaction at Work
- 9.04: Bad Press
- 9.05: Exercises
- 10: Independent Samples
- 10.01: Difference of Means
- 10.02: Research Questions about Independent Means
- 10.03: Hypotheses and Decision Criteria
- 10.04: Independent Samples t-statistic
- 10.05: Standard Error and Pooled Variance
- 10.06: Movies and Mood
- 10.07: Effect Sizes and Confidence Intervals
- 10.08: Homogeneity of Variance
- 10.09: Exercises
- 11: Analysis of Variance
- 11.01: Observing and Interpreting Variability
- 11.1E: Analysis of Variance (Exercises)
- 11.02: Sources of Variance
- 11.03: ANOVA Table
- 11.04: ANOVA and Type I Error
- 11.05: Hypotheses in ANOVA
- 11.06: Scores on Job Application Tests
- 11.07: Variance Explained
- 11.08: Post Hoc Tests
- 11.09: Other ANOVA Designs
- 12: Correlations
- 12.01: Variability and Covariance
- 12.02: Visualizing Relations
- 12.03: Three Characteristics
- 12.04: Pearsons r
- 12.05: Anxiety and Depression
- 12.06: Effect Size
- 12.07: Correlation versus Causation
- 12.08: Final Considerations
- 12.09: Exercises
- 13: Linear Regression
- 13.01: Line of Best Fit
- 13.02: Prediction
- 13.03: ANOVA Table
- 13.04: Hypothesis Testing in Regression
- 13.05: Happiness and Well-Being
- 13.06: Multiple Regression and Other Extensions
- 13.07: Exercises
- 14: Chi-square
- 14.01: Categories and Frequency Tables
- 14.02: Goodness-of-Fit
- 14.03: Statistic
- 14.04: Pineapple on Pizza
- 14.05: Contingency Tables for Two Variables
- 14.06: Test for Independence
- 14.07: College Sports
- 14.08: Exercises