Path To College Mathematics
1st Edition
ISBN: 9780134654409
Author: Martin-Gay, K. Elayn, 1955-
Publisher: Pearson,
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Chapter C, Problem 4ES
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3. Bayesian Inference – Updating Beliefs
A medical test for a rare disease has the following characteristics:
Sensitivity (true positive rate): 99%
Specificity (true negative rate): 98%
The disease occurs in 0.5% of the population.
A patient receives a positive test result.
Questions:
a) Define the relevant events and use Bayes’ Theorem to compute the probability that the patient actually has the disease.b) Explain why the result might seem counterintuitive, despite the high sensitivity and specificity.c) Discuss how prior probabilities influence posterior beliefs in Bayesian inference.d) Suppose a second, independent test with the same accuracy is conducted and is also positive. Update the probability that the patient has the disease.
answer number 6
Chapter C Solutions
Path To College Mathematics
Ch. C - Prob. 1ESCh. C - Prob. 2ESCh. C - Prob. 3ESCh. C - Prob. 4ESCh. C - Prob. 5ESCh. C - Prob. 6ESCh. C - Prob. 7ESCh. C - Prob. 8ESCh. C - Prob. 9ESCh. C - Prob. 10ES
Ch. C - Prob. 11ESCh. C - Prob. 12ESCh. C - Prob. 13ESCh. C - Prob. 14ESCh. C - Prob. 15ESCh. C - Prob. 16ESCh. C - Prob. 17ESCh. C - Prob. 18ESCh. C - Prob. 19ESCh. C - Prob. 20ESCh. C - Prob. 21ESCh. C - Prob. 22ESCh. C - Prob. 23ESCh. C - Prob. 24ESCh. C - Prob. 25ESCh. C - Prob. 26ESCh. C - Prob. 27ESCh. C - Prob. 28ESCh. C - Prob. 29ESCh. C - Prob. 30ESCh. C - Prob. 31ESCh. C - Prob. 32ESCh. C - Prob. 33ESCh. C - Prob. 34ESCh. C - Prob. 35ESCh. C - Prob. 36ESCh. C - Prob. 37ESCh. C - Prob. 38ESCh. C - Prob. 39ESCh. C - Prob. 40ESCh. C - Prob. 41ESCh. C - Prob. 42ESCh. C - Prob. 43ESCh. C - Prob. 44ESCh. C - Prob. 45ESCh. C - Prob. 46ESCh. C - Prob. 47ESCh. C - Prob. 48ESCh. C - Prob. 49ESCh. C - Prob. 50ESCh. C - 12,000 good assembly line products to 40 defective...Ch. C - Prob. 52ESCh. C - Prob. 53ESCh. C - Prob. 54ESCh. C - Prob. 55ESCh. C - Prob. 56ESCh. C - Prob. 57ESCh. C - Prob. 58ESCh. C - Prob. 59ESCh. C - Prob. 60ESCh. C - Prob. 61ESCh. C - Prob. 62ESCh. C - Prob. 63ESCh. C - Prob. 64ESCh. C - Prob. 65ESCh. C - Prob. 66ESCh. C - Prob. 67ESCh. C - Prob. 68ESCh. C - Prob. 69ESCh. C - Prob. 70ES
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- answer number 2arrow_forward4. Linear Regression - Model Assumptions and Interpretation A real estate analyst is studying how house prices (Y) are related to house size in square feet (X). A simple linear regression model is proposed: The analyst fits the model and obtains: • Ŷ50,000+150X YBoB₁X + € • R² = 0.76 • Residuals show a fan-shaped pattern when plotted against fitted values. Questions: a) Interpret the slope coefficient in context. b) Explain what the R² value tells us about the model's performance. c) Based on the residual pattern, what regression assumption is likely violated? What might be the consequence? d) Suggest at least two remedies to improve the model, based on the residual analysis.arrow_forward5. Probability Distributions – Continuous Random Variables A factory machine produces metal rods whose lengths (in cm) follow a continuous uniform distribution on the interval [98, 102]. Questions: a) Define the probability density function (PDF) of the rod length.b) Calculate the probability that a randomly selected rod is shorter than 99 cm.c) Determine the expected value and variance of rod lengths.d) If a sample of 25 rods is selected, what is the probability that their average length is between 99.5 cm and 100.5 cm? Justify your answer using the appropriate distribution.arrow_forward
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