L01 Introduction Flashcards
Two types of systems - is randomness involved?
Deterministic vs Probabilistic
Two types of variation between conditions
Systematic variation
Unsystematic variation
Stats - two ways
Descriptive vs Inferential
Descriptive statistics
Describe data through
- graphs (bar, pie chart)
- numerical - average, range, mean
Inferential statistics
Hypothesis testing
- Differences
- Correlations
- Interactions
Research process
Initial observation Data
->
(Conceptual domain)
Theory
->
Generate Hypothesis -> Identifying variables
->
(Observable domain)
Generate predictions
->
Collect data to test predictions -> Measuring variables
->
Analyse data -> Graph data/ Fit model
——–> Revise theory
Theory - what is it?
Explanation/set of principles
Well substantiated through repeated testing
Broad/variety of phenomena
Conceptual
Hypothesis
A proposed (as yet untested) theory-driven (informed) to explain initial observations /research question narrower focus than a theory
Prediction
Operationalising the hypothesis into a testable statement in order to collect data that proves/disproves it
Observable domain
A good theory?
- FALSIFIABLE/TESTABLE (can be proven/disproven)
- allows us to make a statement about the world
- brings together a range of findings
- data does not conflict with it
Falsification
Karl Popper
“criterion for the scientific status of a theory is its falsifiability/refutability/testability”
Deterministic system
No randomness involved - if x, then y
As opposed to probabilistic system
Probabilistic system
Randomness/chance
if x, then the likelihood of y changes
Predictions in terms of probability with a degree of error involved
Why stats?
To communicate about data.
Identify systematic vs unsystematic variation.
Most systems in the real world are probabilistic.
