Analysis of variance and design of experiment-I - Study24x7

New to Study24X7 ?

139 followers

2 Learners

# Analysis of variance and design of experiment-I

Validity Unlimited All Level English

0.0 (0)
Free

Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between groups) used to analyze the differences among group means in a sample. ANOVA was developed by statistician and evolutionary biologist Ronald Fisher. The ANOVA is based on the law of total variance, where the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical testof whether the population means of several groups are equal, and therefore generalizes the t-test to more than two groups. ANOVA is useful for comparing (testing) three or more group means for statistical significance.

• Total 10 Modules
• 39 Pdfs
• Published on 26 June, 2019

## Some Results on Linear Algebra, Matrix Theory and Distributions

• Lecture1-Module1-Anova-1

10 pages
• Lecture2-Module1-Anova-1

11 pages
• Lecture3-Module1-Anova-1

10 pages

## General Linear Hypothesis and Analysis of Variance

• Lecture4-Module2-Anova-1

9 pages
• Lecture5-Module2-Anova-1

9 pages
• Lecture6-Module2-Anova-1

10 pages
• Lecture7-Module2-Anova-1

10 pages
• Lecture8-Module2-Anova-1

13 pages
• Lecture9-Module2-Anova-1

9 pages
• Lecture10-Module2-Anova-1

10 pages
• Lecture11-Module2-Anova-1

7 pages

## Experimental Design Models

• Lecture12-Module3-Anova-1

10 pages
• Lecture13-Module3-Anova-1

10 pages
• Lecture14-Module3-Anova-1

11 pages
• Lecture15-Module3-Anova-1

8 pages
• Lecture16-Module3-Anova-1

10 pages
• Lecture17-Module3-Anova-1

9 pages
• Lecture18-Module3-Anova-1

9 pages

## Experimental Designs and Their Analysis

• Lecture19-Module4-Anova-1

10 pages
• Lecture20-Module4-Anova-1

10 pages
• Lecture21-Module4-Anova-1

11 pages
• Lecture22-Module4-Anova-1

11 pages
• Lecture23-Module4-Anova-1

9 pages
• Lecture24-Module4-Anova-1

7 pages

## Factorial Experiments

• Lecture25-Module5-Anova-1

10 pages
• Lecture26-Module5-Anova-1

7 pages
• Lecture27-Module5-Anova-1

7 pages
• Lecture28-Module5-Anova-1

8 pages
• Lecture29-Module5-Anova-1

7 pages

## Confounding in Factorial Experiments

• Lecture30-Module6-Anova-1

12 pages
• Lecture31-Module6-Anova-1

9 pages

## Analysis of Covariance

• Lecture32-Module7-Anova-1

13 pages
• Lecture33-Module7-Anova-1

9 pages

## Analysis of Variance in Random-Effects Model and Mixed-Effects Model

• Lecture34-Module8-Anova-1

13 pages
• Lecture35

8 pages

## Analysis of Nonorthogonal Data

• Lecture36-Module9-Anova-1

8 pages
• Lecture37-Module9-Anova-1

8 pages

## Exercises & References

• Lecture38-Module9-Anova-1-Exercises

28 pages
• References-Anova-1

2 pages

4.5 (3)

0.0 (0)

5.0 (1)

0.0 (0)

4.5 (12)

3.0 (1)

5.0 (1)

5.0 (1)

0.0 (0)

5.0 (1)

0.0 (0)

0.0 (0)

5.0 (2)

5.0 (1)

5.0 (2)

5.0 (2)

5.0 (5)

5.0 (10)

0.0 (0)

5.0 (4)

0.0 (0)

0.0 (0)

5.0 (2)

5.0 (1)

0.0 (0)