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Lesson Example Discussion Quiz: Class Homework

Quiz At Home

Title: Baye’s theorem

Grade: 9-a Lesson: S3-L7

Explanation: Hello Students, time to practice and review. Let us take next 10-15 minutes to solve the five problems using the Quiz Sheet. Then submit the quiz to get the score. This is a good exercise to check your understanding of the concepts.

Quiz: at Home

Problem Id	Question	Options
1	The chances of X, Y and Z becoming managers of a certain company are 4 : 2 : 3. The probabilities that bonus scheme will be introduced if X, Y and Z become managers are 0.3, 0.5 and 0.4 respectively. If the bonus scheme has been introduced, what is the probability that Z was appointed as the manager by using bayes theorem.	A) 7/17 B) 6/17 C) 8/17 D) 9/17
2	A consulting firm rents car from three agencies such that 50% from agency L, 30% from agency M and 20% from agency N. If 90% of the cars from L, 70% of cars from M and 60% of the cars from N are in good conditions what is the probability that the firm will get a car in good condition by using bayes theorem.	A) 0.80 B) 0.79 C) 0.78 D) 0.81
3	A consulting firm rents car from three agencies such that 50% from agency L, 30% from agency M and 20% from agency N. If 90% of the cars from L, 70% of cars from M and 60% of the cars from N are in good conditions if a car is in good condition, what is probability that it has come from agency N by using bayes theorem.	A) 0.6 B) 0.5 C) 0.7 D) 2/13
4	The chances of A, B and C becoming manager of a certain company are 5 : 3 : 2. The probabilities that the office canteen will be improved if A, B, and C become managers are 0.4, 0.5 and 0.3 respectively. If the office canteen has been improved, what is the probability that B was appointed as the manager by using bayes theorem .	A) 15/41 B) 16/41 C) 17/41 D) 18/41
5	A doctor is called to see a sick child. The doctor has prior information that 90% of sick children in that neighborhood have the flu, while the other 10% are sick with measles. Let F stand for an event of a child being sick with flu and M stand for an event of a child being sick with measles. Assume for simplicity that F ∪ M = Ω, i.e., that there no other maladies in that neighborhood by using bayes theorem.	A) 0.10 B) 0.09 C) 0.08 D) 0.07

Problem Id

Question

Options

The chances of X, Y and Z becoming managers of a certain company are 4 : 2 : 3. The probabilities that bonus scheme will be introduced if X, Y and Z become managers are 0.3, 0.5 and 0.4 respectively. If the bonus scheme has been introduced, what is the probability that Z was appointed as the manager by using bayes theorem.

A) 7/17
B) 6/17
C) 8/17
D) 9/17

A consulting firm rents car from three agencies such that 50% from agency L, 30% from agency M and 20% from agency N. If 90% of the cars from L, 70% of cars from M and 60% of the cars from N are in good conditions what is the probability that the firm will get a car in good condition by using bayes theorem.

A) 0.80
B) 0.79
C) 0.78
D) 0.81

A consulting firm rents car from three agencies such that 50% from agency L, 30% from agency M and 20% from agency N. If 90% of the cars from L, 70% of cars from M and 60% of the cars from N are in good conditions if a car is in good condition, what is probability that it has come from agency N by using bayes theorem.

A) 0.6
B) 0.5
C) 0.7
D) 2/13

The chances of A, B and C becoming manager of a certain company are 5 : 3 : 2. The probabilities that the office canteen will be improved if A, B, and C become managers are 0.4, 0.5 and 0.3 respectively. If the office canteen has been improved, what is the probability that B was appointed as the manager by using bayes theorem .

A) 15/41
B) 16/41
C) 17/41
D) 18/41

A doctor is called to see a sick child. The doctor has prior information that 90% of sick children in that neighborhood have the flu, while the other 10% are sick with measles. Let F stand for an event of a child being sick with flu and M stand for an event of a child being sick with measles. Assume for simplicity that F ∪ M = Ω, i.e., that there no other maladies in that neighborhood by using bayes theorem.

A) 0.10
B) 0.09
C) 0.08
D) 0.07