Quantitative
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4 important considerations for research topics
• Impact • Environment • Cost/Benefit trade off • Personal interest/development
4 important considerations for research Q
• How unknown is the Q? (answer unknown/different perspective on debate offered) • Impact • Practicality • Literature reviews
How to ensure generalisability
Size - the bigger the better Representativity - think demographics, an accurate picture of society (not e.g. Western centric)
How to ensure causality
Correlation is NOT causation - Manipulation of variables, either through repeated measures or between measures set up
Repeated measures v between measures
e.g. within experiment run - sit - walk (heart rate measurement) RM = same participant used BM = separate participants
What is operationalisation?
Describes when a variable is defined by the researcher and a way of measuring that variable is developed for the research.
What should you consider within operationalisation?
Reliability = the extent to which it produces similar measurements under similar conditions - Can be combatted by increasing sample size and averaging Validity =the extent to which procedure measures what it is truly meant to measure) - Can’t be combatted by increased sample size
What the 3 types of variables to consider in qual. methods
• Musical variables • Scientific variables • Psychological variables
Musical variables
• Computational (algorithm generated) • Human (human evaluation of music e.g. theory) • Symbolic (discrete symbols) • Audio (direct analysis of audio)
Scientific variables
Ordinal (finite set of values with an intrinsic order) Categorical (finite set of values without an intrinsic order e.g. T/F) Continuous (numeric values within a continuous range) - Can be interval (+ & - meaningful e.g. time of day) or ratio (multiplication meaningful e.g. money)
Psychological variables
Manipulations Physical behaviour Neural responses Physiology Latent traits (e.g. personality - usually expressed through questionnaires) Demographics
Ways of measuring neural responses (+ comparison)
EEG - electric - high temporal sensitivity - good to record temporal responses to stimuli - not very precise in location MEG - magnetic - high temporal sensitivity - greater precision fMRI - changes in blood flow in brain - better location - lower temporal sensitivity
comparison of quant v qual
quant - expressed in numbers/graphs - acoustics - generalisable - test/confirm hypothesis - researcher should be neutral (aim for objectivity) qual - expressed in words - researcher integral - understand concepts/ further info (in-depth insights)
advantages/disadvantages of quant
+ generalisable + tests hypothesis + rapid analysis + objectivity • size • context • confirmation bias (search to prove a hypothesis)