Experimental Design: Strategies and Analysis

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Model Formulas in R: Basics and Applications

Explores model formulas in R, covering basics, interactions, ANOVA, and factorial designs with practical examples.

Full Factorial Design Introduction

Covers the basics of full factorial design, coding, graphical outputs, and data analysis.

Factorial Experimental Design

Covers factorial experimental design, 2-way ANOVA, interaction plots, and unbalanced designs.

Model with Interactions

Explains models with interactions, emphasizing the significance of factors and F-values.

Experimental Design and Analysis

Covers the basics of experimental design and analysis, focusing on statistical techniques like ANOVA, regression, mediation, and moderation.

Graphical Analysis of Full Factorials

Explores the graphical analysis of full factorial experiments, emphasizing efficient data analysis and interpretation of main effects and interactions.

Experimental Design: Replication, Randomization, Blocking

Delves into experimental design in genomics, emphasizing replication, randomization, and blocking for reducing bias and controlling variation.

Nested Model Selection

Explores nested model selection in linear models, comparing models through sums of squares and ANOVA, with practical examples.

Linear Regression: Understanding Quantitative Relationships

Covers linear regression, from developing research questions to interpreting R-squared and adding predictors to improve the model.

Fractional Factorial Designs

Explores fractional factorial designs, from types to analysis and model building.