QMMS Flashcards
Correlative
Uses the natural variation to test the effect
of particular factors
Manipulative experiment
To manipulate system in order to look for causal relationships
Base line
‘Natural history’ of investigated organisms must be known
Control
A reference to which results of the experiment are compared
Replication
is a mean to measure and control natural variation
Randomization
refers to the random collection of samples that are representative for the total population
= a mean to control the effects of random variation
Independent variable
The independent variable is the variable the experimenter changes or controls and is assumed to have a direct effect on the dependent variable. … The dependent variable is the variable being tested and measured in an experiment, and is ‘dependent’ on the independent variable.
Traps
Density dependent process, unwanted effects of methods or tools
Factorial
In statistics, a full factorial experiment is an experiment whose design consists of two or more factors, each with discrete possible values or “levels”, and whose experimental units take on all possible combinations of these levels across all such factors.
Randomized block
In the statistical theory of the design of experiments, blocking is the arranging of experimental units in groups (blocks) that are similar to one another. Blocking reduces unexplained variability.
Repeated measures
Repeated measures design is a research design that involves multiple measures of the same variable taken on the same or matched subjects either under different conditions or over two or more time periods. For instance, repeated measurements are collected in a longitudinal study in which change over time is assessed.
Hierarchical nesting
Hierarchically structured data is nested data where groups of units are clustered together in an organized fashion, such as students within classrooms within schools. … For example, student characteristics, such as age and school characteristics, such as graduation rate, can be modeled.
Confounding factor
Factors that interact with both what we
are manipulating and what we are measuring.
Quantitative
Allows you to test hypotheses, expressed in numbers, requires a larger sample size, and is analyzed by math/statistical analysis.
Qualitative
Allows you to formulate hypotheses, is expressed in words, smaller sample sizes required, allows you to summarize, categorize and interpret.
SSE
Sum of Squares ERROR - The error is the value between the observed value and the predicted value
SSR
Sum of Squares REGRESSION - The sum of the differences between the predicted value and the mean of the dependent variable.
SST
Sum of Squares TOTAL - Sum of squares total is the squared differences between the observed dependent variable and the mean.
Matrix
An array of numbers symbolized by bold CAPITAL letters
Order of a Matrix
Dimensions of a matrix always shown as rows x columns (ex: 3x2)
Conformable matrix
Two matrices are conformable if the number of
columns in A equals the number of rows in B
Diagonal matrix
Square matrix with all off-diagonal values equal to zero
Identity matrix
Diagonal matrix where the diagonal elements all equal one
Null matrix
All elements in the matrix equal zero
Parametric model
models that include mathematical quantities (parameters) that are required to be estimated (by measurements)
Dynamic models
Models for which variables are expressed to change in time
Existence and Unicity of the solution
refer to the Cauchy-Liebniz Theorem for dynamic models
Identifiability
for one given solution of the model, there is only one unique vector of parameters
Observability
From one solution of the model only one vector of parameters can be estimated
Discernability
A model is discernable if the solution for one set of parameters is different to any other solutions calculated by another model
Optimisation
procedure that allows to find the best parameters value from available data according to a pre-defined criteria
Continuous data
set of data is said to be continuous if the values belonging to the set can take on ANY value within a finite or infinite interval.
Discrete data
A set of data is said to be discrete if the values belonging to the set are distinct and separate (unconnected values)
Response variable
A Response Variable (or dependent variable) is that variable whose variation depends on other variables. … In short, the response variable is the subject of change within an experiment, often as a result of differences in the explanatory variables.
Binary data response variable
Probability distribution will be binomial
Count data as response variable
Probability distribution will be Poisson
Parametric test
Parametric tests are those that make assumptions about the parameters of the population distribution from which the sample is drawn. This is often the assumption that the population data are normally distributed.
Non-parametric test
A non parametric test (sometimes called a distribution free test) does not assume anything about the underlying distribution (for example, that the data comes from a normal distribution).
