Chapter V analysis of variance
What test indicators?
Is to measure the value of statistics, EG : height and weight
Test Unit ( Experimental Unit ) What is?
Experimental carrier, such as a mouse
What are party is?
It is the variance
Stochastic model What are the characteristics τ?
The standard normal distribution
Relatively fixed model and the stochastic model
The biggest difference is the study of the mean fixed model; stochastic model study τ
Variance analysis results should be noted that?
To compare 0.01 and 0.05 , to see whether significant or highly significant
Letter notation determination principle?
Among the average, where there is the difference between a mark same letter is not significant, i.e. where the difference labeled with letters are significantly different. As long as there exists the same letter are not considered significant.
LSR key methods are:
q inspection and LSR difference?
q-test and LSD and LSR merits?
q-test strict
LSD can look at a relationship level with any other level of
LSR look at the overall situation is relatively fast
Duplicate analysis of variance values and the difference between the value of the analysis of variance did not repeat that?
Fixed model consistent, but a different random and mixture models:
To make up for missing data principles?
So that after obtaining the missing data, the minimal errors.
After the freedom to make up for missing values What changed?
Complement a missing value minus one degree of freedom, two complement missing values minus two degrees of freedom, because when evaluated using the known information missing values, the constraint is increased.
What can be additive variance analysis is?
Effect can be dismantled
Analysis of Variance three premises:
Normal; additivity; homogeneity of variance
Square root conversion for?
Poisson positive state
To-digital conversion for?
Additive effect strong, but proportional to, the number of available turned adder
Arc sine transformation for?
Percentage into the binomial distribution