HLTH 501 BIOSTATISTICS EXAM STUDY
SHEET INCLUDING ALL ACTUAL EXAM
QUESTIONS AND SOLUTIONS 2026.
⫸ define data. Answer: the collection of raw facts, observations, or
measurements
⫸ define biostatistics. Answer: stats related to healthcare outcomes,
living organisms, and disease
⫸ population vs sample. Answer: -population- The entire group you
want to study.
*Ex All PA students in the U.S.
-Sample- A smaller group taken from the population to represent it.
*Ex100 PA students randomly chosen from the U.S.
⫸ sampling error. Answer: sample does not accurately reflect
population
⫸ how to avoid sampling error. Answer: increase sample size
⫸ selection bias. Answer: Systematic error in how subjects are
chosen.
, ⫸ how to avoid selection bias. Answer: random sampling
⫸ why use samples instead of whole population?. Answer: -Faster
(population takes too long)
-Cheaper (population costs too much)
-Practical (can't measure everyone)
-Accurate enough (a well-chosen sample represents population)
⫸ simple random sampling. Answer: -Simple- Everyone in
population has equal chance of being picked.
*Ex Put all names in a hat, draw at random.
⫸ stratified random sampling. Answer: Stratified- Population is split
into subgroups(stratas), then Randomly sample within each group.
⫸ cluster sampling. Answer: -Divide into clusters
-Randomly pick entire clusters
*Ex Randomly pick 5 schools, survey all students in those schools.
⫸ what makes a good variable. Answer: -reliable and valid
-low bias
-feasible/practical
-low cost
-objective and clear
SHEET INCLUDING ALL ACTUAL EXAM
QUESTIONS AND SOLUTIONS 2026.
⫸ define data. Answer: the collection of raw facts, observations, or
measurements
⫸ define biostatistics. Answer: stats related to healthcare outcomes,
living organisms, and disease
⫸ population vs sample. Answer: -population- The entire group you
want to study.
*Ex All PA students in the U.S.
-Sample- A smaller group taken from the population to represent it.
*Ex100 PA students randomly chosen from the U.S.
⫸ sampling error. Answer: sample does not accurately reflect
population
⫸ how to avoid sampling error. Answer: increase sample size
⫸ selection bias. Answer: Systematic error in how subjects are
chosen.
, ⫸ how to avoid selection bias. Answer: random sampling
⫸ why use samples instead of whole population?. Answer: -Faster
(population takes too long)
-Cheaper (population costs too much)
-Practical (can't measure everyone)
-Accurate enough (a well-chosen sample represents population)
⫸ simple random sampling. Answer: -Simple- Everyone in
population has equal chance of being picked.
*Ex Put all names in a hat, draw at random.
⫸ stratified random sampling. Answer: Stratified- Population is split
into subgroups(stratas), then Randomly sample within each group.
⫸ cluster sampling. Answer: -Divide into clusters
-Randomly pick entire clusters
*Ex Randomly pick 5 schools, survey all students in those schools.
⫸ what makes a good variable. Answer: -reliable and valid
-low bias
-feasible/practical
-low cost
-objective and clear
