Канал: StatDOE by Rosane Rech

How to calculate the real-world values of the variable in central composite designs.

How to calculate the real-world values of the variable in central composite designs.

Design of Experiments for Mixtures

Design of Experiments for Mixtures

RSM 08 Desirable features for Experimental Designs

RSM 08 Desirable features for Experimental Designs

RSM 07 Analyzing a Central Composite Design in R

RSM 07 Analyzing a Central Composite Design in R

RSM 06 Central Composite Design

RSM 06 Central Composite Design

RSM 05 Designs with Central Points - Interpreting a significant lack-of-fit

RSM 05 Designs with Central Points - Interpreting a significant lack-of-fit

RSM 04 Method of the Steepest Ascent

RSM 04 Method of the Steepest Ascent

RSM 03 Analyzing a 2ˆ2 Factorial Design with Central Points - R tutorial

RSM 03 Analyzing a 2ˆ2 Factorial Design with Central Points - R tutorial

RSM 02 The starting design: 2ˆ2 Factorial Designs with Central Points

RSM 02 The starting design: 2ˆ2 Factorial Designs with Central Points

RSM 01 Introduction to Response Surface Methodology

RSM 01 Introduction to Response Surface Methodology

Building a Pie-Donut Chart in R

Building a Pie-Donut Chart in R

Add and position letters indicating significant differences in bar plots

Add and position letters indicating significant differences in bar plots

Desirability functions

Desirability functions

Barplots for the Results of a Three-Factor Experiment

Barplots for the Results of a Three-Factor Experiment

Boxplot with Letters Indicating Significant Differences

Boxplot with Letters Indicating Significant Differences

Publication-Quality Scatterplots for Two Factors with ggplot - Two-Way ANOVA with R - tutorial 4

Publication-Quality Scatterplots for Two Factors with ggplot - Two-Way ANOVA with R - tutorial 4

Publication-Quality Barplots for Two Factors with ggplot - Two-Way ANOVA with R - tutorial 3

Publication-Quality Barplots for Two Factors with ggplot - Two-Way ANOVA with R - tutorial 3

Tukey's Test and Letters to Indicate Significant Differences - Two-Way ANOVA with R - tutorial 2

Tukey's Test and Letters to Indicate Significant Differences - Two-Way ANOVA with R - tutorial 2

Two-Way ANOVA with R - Analysis of Variance

Two-Way ANOVA with R - Analysis of Variance

[COURSE] Design of Experiments for Optimisation

[COURSE] Design of Experiments for Optimisation

One Way ANOVA 4 - Bar Plots Coloured According Tukey's Test using ggplot

One Way ANOVA 4 - Bar Plots Coloured According Tukey's Test using ggplot

One-Way ANOVA 3 - Using Superscript Letters in Tukey's Test

One-Way ANOVA 3 - Using Superscript Letters in Tukey's Test

One-Way ANOVA R tutorial 2 - Tukey's Test

One-Way ANOVA R tutorial 2 - Tukey's Test

One-Way ANOVA R-tutorial 1 - Analysis of Variance

One-Way ANOVA R-tutorial 1 - Analysis of Variance

DoE 67: Final Visualization of the Results - ggplot package

DoE 67: Final Visualization of the Results - ggplot package

DoE 64: Building Fractional Designs in R - FrF2 package

DoE 64: Building Fractional Designs in R - FrF2 package

DoE 63: One-Quarter Fraction of the 2ˆk Designs

DoE 63: One-Quarter Fraction of the 2ˆk Designs

Design and Analysis of Experiments

Design and Analysis of Experiments

DoE 32: Analysing a 2^2 fatorial design in R

DoE 32: Analysing a 2^2 fatorial design in R

Choosing an Experimental Design

Choosing an Experimental Design

RSM: Building Central Composite Design in R - function "ccd"

RSM: Building Central Composite Design in R - function "ccd"

RSM: Building Central Composite Designs in R - functions: cube, djoin, star

RSM: Building Central Composite Designs in R - functions: cube, djoin, star

RSM: Desirable Features for Experimental Designs

RSM: Desirable Features for Experimental Designs

RSM: Central Composite Design: R tutorial

RSM: Central Composite Design: R tutorial

RSM: Introduction to Response Surface Methodology

RSM: Introduction to Response Surface Methodology

LRM 5: Inaccurate Levels in Design Factors - Part 1

LRM 5: Inaccurate Levels in Design Factors - Part 1

LRM 6: Inaccurate Levels in Design Factors - Part 2

LRM 6: Inaccurate Levels in Design Factors - Part 2

LRM 4: Multiple Linear Regression Models

LRM 4: Multiple Linear Regression Models

LRM 3: Building Linear Models in R

LRM 3: Building Linear Models in R

LRM 2: Fitting Linear Models to Experimental Data

LRM 2: Fitting Linear Models to Experimental Data

LRM 1: Introduction to Linear Regression Models

LRM 1: Introduction to Linear Regression Models

DoE 21: Solving a Two Factor Factorial Design Using Excel

DoE 21: Solving a Two Factor Factorial Design Using Excel

DoE 11: One-Way ANOVA in Excel Tutorial

DoE 11: One-Way ANOVA in Excel Tutorial

DoE 36: Building and Interpreting Contour Plots in R

DoE 36: Building and Interpreting Contour Plots in R

DoE 06: MS Excel Tutorial for t-test

DoE 06: MS Excel Tutorial for t-test

DoE 02: Basic Principles of the Design of Experiments

DoE 02: Basic Principles of the Design of Experiments

DoE 01: Introduction to the Design of Experiments

DoE 01: Introduction to the Design of Experiments