Model Formulas in R: Basics and Applications

Related lectures (32)

Page 3 of 4

Covers statistical frequency, binning, histograms, and R data analysis basics.

Explores qualitative factors in Design of Experiments, including statistical tests and error types.

Explores exploiting redundancies, confounding effects, and analyzing fractional factorials in experimental designs.

Explores model building using analysis of means for predicting factors' effects and interactions.

Introduces model-based clustering methods using mixture models and latent variables, with practical examples on iris data.

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

Explores fractional factorial design basics, including blocking alias, interaction effects, and design comparison.

Covers the basics of Vectorworks software and attributes like fill types and shadow settings.

Covers topics in Quantum Chemistry, including history, tools, color & draw techniques, shapes, and mathematical conversions.

Covers linear regression coefficients, confidence intervals, and R's calculation methods.