RM - Intro to Design + Data Flashcards
WithinControl Condition
Helps understand the role of the IV + rule out alternative explanations for results
Extraneous Variable.
Not controlled in the experiment, could effect the DV - unlikely to change the direction of the effect
Confounding Variables
Extraneous variable that varies systematically with the IV to influence the DV
E.g. Every Monday class there is a football match outside
Likely to influence the results change the direction of events
Between subject Experimental design
Either in 1 condition or the other
Each ppt contributes to 1 data point
Between subject design benefits
1) Avoids pt/experimenter effects
2) Avoids order+ fatigue effects
Between subject design disadvantages
1) Takes longer
2) Is less powerful
3) Introduces variation due to indiv differences
within subject design
Takes part in both conditions compare your score in 1 condition and another
Within subject design Benefits
1) Accounts for indiv differences
2) cost + time effective (recruit half as many ppt)
within subject design disadvantage
order effects and fatigue Effects
Matched pairs Design
Different ppt in all conditions, ppts matched e.g Twin Studies
Matched pairs Design Benefit
1) Accounts for indiv differences
Matched pairs Design Disadvantage
Difficult to match people accurately so matched on what is relevant to the experiment
categorical Data
nominal and ordinal
labels
can be called discrete
Nominal categorical Data
No hierarchical order
can be presented as frequencies
ordinal categorical Data
Have hierarchy
e. g illness stage
Numerical/continuous data
Presented as means and standard deviations in text, graph or table
Interval continuous data
scalar that has no meaningful zero
Temperature
Ratio continuous data
scalar with an absolute data, time, heartrate
Standard Error
standard deviation divided by square root of N
Z scores
Standardised score
represents datapoints relationship to the mean
useful when comparing ppts or conditions
useful when the units differ (scores out of 10 VS 25
Z score equation
(score-mean)/Standard deviation
