BCPS EXAM SCRIPT FULL QUESTIONS WITH
EXPERT VERIFIED ANSWERS
●● specificity formula
Answer: Specificity = True negative/(true negative + false positive)
●● precision definition
Answer: how consistent the test results are
●● accuracy formula
Answer: "accuracy=(true positive plus true negative)/total - how true the
test results are"
●● receiver operator characteristic
Answer: "the cutoff value for maximizing accuracy; describes the
inverse relationship between sensitivity and specificity (i.e. increasing
specificity decreases sensitivity)"
●● positive predictive value formula
Answer: PPV=True positive/(true positive +false positive)
●● negative predictive value formula
,Answer: NPV= true negative/(true negative + false negative)
●● prevalence definition
Answer: total number of cases at a given time
●● incidence definition
Answer: new cases in a specfiic time peiod
●● likelihood ratio formula
Answer: "positive test =true positive %/ false positive% OR negative
test =false negative %/true negative % "
●● when is a 95% CI statistically significant
Answer: "for mean: if it doesn't cross 0; For OR/RR, if it doesn't cross
1"
●● When is RR done
Answer: prospective studies
●● When is OR done
Answer: retrospective studies (would overestimate the risk in
prospective studies unless incidence in population is <10%)
, ●● RR formula
Answer: RR=incidence rate in exposed patients/ incidence rate in non-
exposed patients
●● if RR >1, what does that mean
Answer: the incidence in the exposed group is higher than non-exposed
group
●● Odds Ratio Formula
Answer: OR = (# of exposed with disease present X # of unexposed with
disease absent)/(# of exposed with disease absent x # of unexposed with
disease present)
●● what looks at predictability?
Answer: regression analysis, not correlation coefficient
●● coefficient of variation (r squared) definition
Answer: this provides us with the %of information we can attribute from
one variable to another
●● linear regression vs multilinear regression
Answer: linear is 1:1 independent to dependent variables, whereas
multilinear is multiple:1 independient to dependent variables
EXPERT VERIFIED ANSWERS
●● specificity formula
Answer: Specificity = True negative/(true negative + false positive)
●● precision definition
Answer: how consistent the test results are
●● accuracy formula
Answer: "accuracy=(true positive plus true negative)/total - how true the
test results are"
●● receiver operator characteristic
Answer: "the cutoff value for maximizing accuracy; describes the
inverse relationship between sensitivity and specificity (i.e. increasing
specificity decreases sensitivity)"
●● positive predictive value formula
Answer: PPV=True positive/(true positive +false positive)
●● negative predictive value formula
,Answer: NPV= true negative/(true negative + false negative)
●● prevalence definition
Answer: total number of cases at a given time
●● incidence definition
Answer: new cases in a specfiic time peiod
●● likelihood ratio formula
Answer: "positive test =true positive %/ false positive% OR negative
test =false negative %/true negative % "
●● when is a 95% CI statistically significant
Answer: "for mean: if it doesn't cross 0; For OR/RR, if it doesn't cross
1"
●● When is RR done
Answer: prospective studies
●● When is OR done
Answer: retrospective studies (would overestimate the risk in
prospective studies unless incidence in population is <10%)
, ●● RR formula
Answer: RR=incidence rate in exposed patients/ incidence rate in non-
exposed patients
●● if RR >1, what does that mean
Answer: the incidence in the exposed group is higher than non-exposed
group
●● Odds Ratio Formula
Answer: OR = (# of exposed with disease present X # of unexposed with
disease absent)/(# of exposed with disease absent x # of unexposed with
disease present)
●● what looks at predictability?
Answer: regression analysis, not correlation coefficient
●● coefficient of variation (r squared) definition
Answer: this provides us with the %of information we can attribute from
one variable to another
●● linear regression vs multilinear regression
Answer: linear is 1:1 independent to dependent variables, whereas
multilinear is multiple:1 independient to dependent variables
