Bayes' Theorem is primarily used to calculate: MCQ with Answer and Explanation
Question
Report Error
Discuss this Question (0)
Practice More Statistics Questions
Question #1
Report Error
A medical test has 95% sensitivity and 90% specificity. If disease prevalence is 1%, the probability that a person with a positive test actually has the disease is approximately:
Correct Answer: Option A
Explanation:
Using Bayes: P(Disease|Positive) = [Sensitivity × Prevalence] / [Sensitivity×Prev + (1-Specificity)×(1-Prev)] = (0.95×0.01) / (0.95×0.01 + 0.10×0.99) = 0.0095 / (0.0095 + 0.099) = 0.0095/0.1085 ≈ 0.0876 ≈ 8.7%. Highlights low positive predictive value when prevalence is low.
Using Bayes: P(Disease|Positive) = [Sensitivity × Prevalence] / [Sensitivity×Prev + (1-Specificity)×(1-Prev)] = (0.95×0.01) / (0.95×0.01 + 0.10×0.99) = 0.0095 / (0.0095 + 0.099) = 0.0095/0.1085 ≈ 0.0876 ≈ 8.7%. Highlights low positive predictive value when prevalence is low.
This question belongs to:
Accountancy and Statistics
Statistics
Question #2
Report Error
General Fertility Rate (GFR) is expressed per:
Correct Answer: Option D
Explanation:
GFR = (Live births in a year / Mid-year population of women aged 15-49) × 1,000, standardizing fertility measurement to the population at risk of childbearing.
GFR = (Live births in a year / Mid-year population of women aged 15-49) × 1,000, standardizing fertility measurement to the population at risk of childbearing.
This question belongs to:
Accountancy and Statistics
Statistics
Question #3
Report Error
For two attributes A and B, the relationship (AB) + (Aβ) equals:
Correct Answer: Option D
Explanation:
The total frequency of attribute A is the sum of those possessing both A and B, and those possessing A but lacking B.
The total frequency of attribute A is the sum of those possessing both A and B, and those possessing A but lacking B.
This question belongs to:
Accountancy and Statistics
Statistics
No comments yet. Be the first to start the discussion!