variables, hypotheses & measurement Flashcards
IV
the presumed cause
manipulated by researchers
ex. workload
DV
outcome or effect
changes bc of iv
ex. stress levels
hypotheses
a testable proposition based on theory and/or observations
- must be testable as without being testable it cannot be provable or disprovable
conceptualization
Defining what a concept means (theoretical level)
operationalization
Defining how to measure a concept (empirical level)
validity
The extent to which a measure captures what it is intended to measure
reliability
The consistency or repeatability of a measurement
systematic error
Bias in measurement that skews data in a particular direction
random error
Non-directional, unpredictable fluctuations in measurement.
why are conceptualization and operationalization necessary for rigorous research
they ensure that abstract concepts are clearly defined and translated into measurable variables, allowing researchers to collect reliable and valid data
validity and reliability in constructing a survey on mental health
validity (Does the survey measure what it intends to measure?) -> social desirability bias, poorly defined questions
reliability (Does the survey produce consistent results over time?) -> test-retest (inconsistent results over time), interrater reliability
is systematic error or random error typically more concerning for researchers trying to avoid bias
Systematic errors are much more problematic than random errors because they can skew your data to lead you to false conclusions
sample statistics
Means, medians, standard deviations, and other numerical values that describe a study’s sample and are usually meant to estimate parameters in the target population
population parameters
- Means, medians, standard deviations, and other numerical values that summarize the characteristics of a population
When researchers cannot observe the actual population parameters, they generate statistics from a sample of that population to estimate them
