KNES 213 EXAMINERS LATEST SET QUESTIONS AND
ANSWERS SURE A+
✔✔Common errors to avoid: correlation proves causation - ✔✔Correlation shows
association only. Causation requires manipulation, temporal precedence, and ruling out
confounds
✔✔Common errors to avoid: p=0.03 means a 97% chance effect is real - ✔✔A p-value
is not a probability about the hypothesis. It is the probability of these data (or more
extreme) assuming H is true
✔✔Common errors to avoid: failing to reject H proves no effect exists - ✔✔It only means
the data were insufficient. Underpowered studies frequently fail to detect genuine
effects.
✔✔Common errors to avoid: this expert said so, therefore it is true - ✔✔Evaluate the
relevance of the authority's expertise to the specific claim. Popularity and social media
reach are irrelevant
✔✔Common errors to avoid: member checking confirms our findings are correct -
✔✔Member checking addresses credibility (truthful representation of participants views)
it does not establish transferability or confirmability
, ✔✔Common errors to avoid: adding more items will fix a low cronbachs alpha -
✔✔Adding poorly designed items does not reliability improve alpha. Items must
coherently measure the same construct
✔✔Common errors to avoid: the standard deviation tells us the typical value - ✔✔SD
measures spread, not central tendency. For skewed data with outliners, use the
median, not the mean
✔✔ Correlation vs causation - ✔✔A correlation indicates a statistical relationship-it does
not establish that on variable causes the other.
✔✔Before inferring causation ask: - ✔✔Was there experimental manipulation and
random assignment? Could be a confounding variable
✔✔Confounding variable - ✔✔Associated with both the independent and dependant
variable
✔✔Research paradigms - ✔✔Positivism, Interpretivism, pragmatism, two-eyed seeing
✔✔Positivism core assumption - ✔✔Objective reality; knowledge through empirical
measurement
✔✔Positivism typical method - ✔✔Quantitative, hypothesis-testing
✔✔Interpretivism core assumption - ✔✔Reality is subjective; focus on lived meaning
✔✔Interpretivism typical method - ✔✔Qualitative, inductive
✔✔Pragmatism core assumption - ✔✔No single methodology has a monopoly on truth;
use whatever best answers the question
✔✔Pragmatism typical method - ✔✔Mixed methods
✔✔Two-eyed seeing core assumptions - ✔✔Indigenous and western knowledge
systems are both valid and complementary
✔✔Two-eyed seeing typical method - ✔✔Integrated
✔✔Epistemology asks what - ✔✔What counts as valid knowledge? (E.g., do subjective
athlete reports or only objective biomarkers constitute evidence?)
✔✔Ontology asks what - ✔✔What is the nature of the phenomenon itself? (E.g., is
overtraining syndrome an objective biological state or a socially constructed
experience?)
ANSWERS SURE A+
✔✔Common errors to avoid: correlation proves causation - ✔✔Correlation shows
association only. Causation requires manipulation, temporal precedence, and ruling out
confounds
✔✔Common errors to avoid: p=0.03 means a 97% chance effect is real - ✔✔A p-value
is not a probability about the hypothesis. It is the probability of these data (or more
extreme) assuming H is true
✔✔Common errors to avoid: failing to reject H proves no effect exists - ✔✔It only means
the data were insufficient. Underpowered studies frequently fail to detect genuine
effects.
✔✔Common errors to avoid: this expert said so, therefore it is true - ✔✔Evaluate the
relevance of the authority's expertise to the specific claim. Popularity and social media
reach are irrelevant
✔✔Common errors to avoid: member checking confirms our findings are correct -
✔✔Member checking addresses credibility (truthful representation of participants views)
it does not establish transferability or confirmability
, ✔✔Common errors to avoid: adding more items will fix a low cronbachs alpha -
✔✔Adding poorly designed items does not reliability improve alpha. Items must
coherently measure the same construct
✔✔Common errors to avoid: the standard deviation tells us the typical value - ✔✔SD
measures spread, not central tendency. For skewed data with outliners, use the
median, not the mean
✔✔ Correlation vs causation - ✔✔A correlation indicates a statistical relationship-it does
not establish that on variable causes the other.
✔✔Before inferring causation ask: - ✔✔Was there experimental manipulation and
random assignment? Could be a confounding variable
✔✔Confounding variable - ✔✔Associated with both the independent and dependant
variable
✔✔Research paradigms - ✔✔Positivism, Interpretivism, pragmatism, two-eyed seeing
✔✔Positivism core assumption - ✔✔Objective reality; knowledge through empirical
measurement
✔✔Positivism typical method - ✔✔Quantitative, hypothesis-testing
✔✔Interpretivism core assumption - ✔✔Reality is subjective; focus on lived meaning
✔✔Interpretivism typical method - ✔✔Qualitative, inductive
✔✔Pragmatism core assumption - ✔✔No single methodology has a monopoly on truth;
use whatever best answers the question
✔✔Pragmatism typical method - ✔✔Mixed methods
✔✔Two-eyed seeing core assumptions - ✔✔Indigenous and western knowledge
systems are both valid and complementary
✔✔Two-eyed seeing typical method - ✔✔Integrated
✔✔Epistemology asks what - ✔✔What counts as valid knowledge? (E.g., do subjective
athlete reports or only objective biomarkers constitute evidence?)
✔✔Ontology asks what - ✔✔What is the nature of the phenomenon itself? (E.g., is
overtraining syndrome an objective biological state or a socially constructed
experience?)
