Full List of Statistically Speaking Stat’s Amore Trainings

Library of Stat’s Amore Trainings in Statistically Speaking

  • Difference in Differences
  • Classic Experimental Designs
  • ANOVA Post-hoc Tests: Practical Considerations
  • Matrix Algebra for Data Analysts: A Primer
  • Moving to a World Beyond p<0.05
  • A (Gentle) Introduction to k-Nearest Neighbor
  • An Introduction into the Grammar of Graphics
  • Writing Study Design and Statistical Analysis Plans
  • Statistical Contrasts
  • Model Fit Statistics (Oh My Goodness!)
  • Choosing the Best Statistical Analysis
  • A Gentle Introduction To Random Slopes In Multilevel Models
  • Missing Data
  • Preparing to Use (and Interpret) a Linear Regression Model
  • Using Open Data in Research: Opportunities and Challenges
  • Inference and p-values and Statistical Significance, Oh My!
  • Explaining Logistic Regression Results to Non-Researchers
  • A Guide to Latent Variable Models
  • Data Cleaning
  • Seven Fundamental Tests for Categorical Data
  • Practical Suggestions for Improving Your Scatterplots
  • Confusing Statistical Terms
  • A Gentle Introduction to Multilevel Models
  • The Anatomy of an ANOVA Table
  • How to Avoid Some Common Graphical Mistakes
  • Practical Advice for Establishing Reliability and Validity
  • Reporting Structural Equation Modeling Results
  • Interpretation of Effect Size Statistics
  • Elements of Experimental Design
  • Writing Up Statistical Results: Basic Concepts and Best Practices
  • A Predictive Modeling Primer: Regression and Beyond
  • Multiple Imputation for Missing Data
  • Non-Parametric Analyses
  • Determining Levels of Measurement: What Lies Beneath the Surface
  • What’s the Best Statistical Package for You?
  • Model Building Approaches
  • Those Darn Ratios!
  • Meta-analysis
  • Latent Growth Curve Analysis
  • Generalized Linear Models
  • Power Analysis and Sample Size Determination Using Simulation
  • Logistic Regression for Count and Proportion Data
  • The Fundamentals of Sample Size Calculations
  • Adjustments for Multiple Testing? When and How to Handle Multiplicity
  • Tests of Equivalence and Non-Inferiority
  • Using Transformations to Improve Your Linear Regression Model
  • Marginal Means, Your New Best Friend
  • A Primer on Exponents & Logarithms for the Data Analyst
  • Model Fit Statistics in Structural Equation Modeling
  • A Data Analyst’s Guide to Methods and Tools for Reproducible Research
  • A Quick Introduction to Weighting in Complex Samples
  • Quantile Regression: Going Beyond the Mean
  • Making Sense of Statistical Distributions
  • The Multi-Faceted World of Residuals
  • Mediated Moderation and Moderated Mediation: What’s the Difference?
  • Crossed and Nested Factors
  • Segmented Regression
  • Statistical Rules of Thumb
  • Confirmatory Factor Analysis
  • Communicating Statistical Results to Non-Statisticians
  • A Gentle Introduction to Generalized Linear Mixed Models – Part 2
  • The LASSO Regression Model
  • A Gentle Introduction to Generalized Linear Mixed Models
  • Cox Regression
  • Small Sample Statistics
  • Working with Truncated and Censored Data
  • Zero Inflated Models
  • Communicating Statistical Results: When to Use Tables vs Graphs to Tell the Data’s Story
  • An Introduction to Kaplan-Meier Curves
  • Inter-Rater Reliability
  • (Just About) Everything You Need To Know Before Starting a Survey
  • Analysis of Ordinal Variables — Options Beyond Nonparametrics
  • A Gentle Introduction to Propensity Score Adjustments and Analysis
  • Mixture Models in Longitudinal Data Analysis
  • Correspondence Analysis
  • Smoothing
  • Latent Class Analysis
  • An Overview of Effect Size Statistics and Why They Are So Important
  • A Gentle Introduction to Bayesian Data Analysis
  • Transformations and Nonlinear Effects in Linear Models
  • Confidence Intervals
  • Count Models
  • Probability Rules and Applications
  • ANCOVA (Analysis of Covariance)
  • Introduction to Time Series Analysis
  • ROC Curves
  • Resampling Techniques
  • Dummy and Effect Coding
  • Classification and Regression Trees
  • Multiple Comparisons
  • Cluster Analysis: Hierarchical and KMeans
  • Introduction to Structural Equation Modeling
  • Multicollinearity
  • Discrete Time Event History Analysis
  • Interactions in ANOVA and Regression Models, Part 2
  • Interactions in ANOVA and Regression Models
  • Complex Survey Sampling — An Overview
  • Mediation
  • Outliers and Influential Points
  • Item Response Theory and Rasch Models
  • Measures of Association: Beyond Pearson’s Correlation
  • MANOVA
  • Using Excel to Graph Predicted Values from Regression Models
  • Hierarchical Regressions
  • Exploratory Factor Analysis
  • Types of Regression Models and When to Use Them