Design Basics Flashcards
Type I Error:
his is the event of rejecting the null hypothesis when it is true. It
is a false positive, saying there are differences when in fact there are no differences.
The probability that a Type I error occurs is denoted by α (“alpha”).
Type II Error:
This is the event of not rejecting the null hypothesis when it is
false. It is a false negative, saying there are not any differences when in fact there
are differences. The probability that a Type II error occurs is denoted by β.
Power:
1−β is the probability of rejecting the null hypothesis when it is false; that
is, saying there are differences when in fact there are differences.
ES
is the effect size, which is the size of the differences between treatments one
wishes to detect.
Important features of an experiment (5)
- The null hypothesis is: H0 : The yield is not affected by seeding rate
- There are 5 treatments (the seeding rates)
- The plot is the experimental unit
- The plot is the sampling unit
- The plots are arranged in a rectangular array of 4 rows by 5 columns
Regression analysis is for when the explanatory variable and response variable are what type of data?
Continuous data.
ANOVA (analysis of variance) Are used when
the explanatory variables are categorical in nature.
ANCOVA (analysis of co-variance), what type of data
Mixture of continuous and categorical data.
The experimental unit is defined as:
The smallest unit to which a treatment has been randomised.
The observational sampling unit is;
The unit of which the measurement is/ was made. This may or may not be the same as the experimental unit.
Steps to find observational and experimental units.
- Ask yourself what are the treatments?
- Ask yourself what the treatments are randomised to to find the experimental units.
- Ask yourself what is being measured to find the observational units. (Ps it’s not the actual unit of measurement it’s the thing/animal that is being measured)
Replicates
Repeat measurements,
A response variable is also refferred to as a
Dependent variable
Explanatory variables are also referred to as
Independent variables