Lecture 2 - Principles of Experimental Designs I Flashcards
What is causation?
When one factor directly affects aother factor
What are two important factors to show causation?
- Changing the first thing produces a change in the second
- There is no other possible cause for the change in the second thing (rule out alternatice explanations or hypotheses)
What is a population?
Components of an experiment
Members of a specific group, defined by purpose of the experiment
What is a sample?
Components of an experiment
Relatively small subset of a population that is selected to represent the population
What is a repreentative sample?
Components of an experiment
Characteristics and behaviour of the sample reflect those of the population (insures generalisability)
Representative sampling is achieved by…?
Random sampling
What is random sampling?
- Members selected in an unbiased manner
- All members have equal chance of selection
What are descriptive statistics?
Summaries of the data collected from the sample e.g. averages
What are inferential statistics?
Generalises from the sample to the population. How likely the effect that you have obtained in your sample is to actually occur in the population e.g. t-tests
What is the dependant variable (DV)?
AKA measured variable
- The measurement taken
- What you record
What does operational definition mean?
Specification of how the property of interest will be measured. In many cases there is no direct way to measure what you want e.g. honesty, happiness, intelligence so you need to think about two things
What two things do you need to think about for operational definition?
- The property of interest (what you are trying to measure e.g. intelligence)
- The dependent variable (a measureable value that must indirectly reflece the property of intrest e.g. score on IQ test)
The indirect measure (DV) is the operational definition of your property of interest
What is validity?
- A DV is valid if it measures what it is supposed to
- Threat to validity arises from any unintended component that is reflected in a score
What is reliability?
- A DV is reliable if, under the same conditions, it gives the same measure, and contains a minimum of measurement error
- Unreliable data reflect error and provide a biased perspective
- If a measure lacks reliability, it also lacks validity
What is bias in terms of the DV?
A biased DV is consistently inaccurate in one direction (i.e. always high or always low)
What makes a good DV?
- Validity
- Reliability
- Unbiased
What are the floor and ceiling effects?
- Ceiling effect is when a task is so easy that all scores are very high
- Floor effect is when a task is so difficult that all scores are very low
What is data type?
- The data type determines what sorts of analyses you can perform on your data and the conclusions you can draw
- Data types are associated with different scales of measurement
- The type of scale of measurement dictates the type of conclusion that you can draw
What is the ordinal scale?
- Categorises and orders the categories
- Bigger means more
- Distance between points on the scale not considered equal e.g. rugby team standings
What is the nominal scale?
- Categorises without ordering
- # s that substitute for names e.g. gender 1 = female, 2 = male
What is the interval scale?
- Categorises, orders, and establishes an equal unit of measurement in the scale
- Knowing hoe much more
- Distance between points on the scale considered equal e.g. celsius temperature
What is the ratio scale?
- Categorises, orders, establishes an equal unit in the scale, and contains a true zero point
- Allows ratio statements e.g. “twice as big”
- e.g. # of items recalled in a memory task (could be zero recalled)
