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g100num [7]
2 years ago
12

If you roll two six-faced dice together, you will get 36 possible outcomes. 4 pts 1. List all possible outcomes of the experimen

t. 2 pts 2. What is the probability of getting a sum of 11 in these outcomes? 2 pts 3. What is the probability of getting a sum less than or equal to 4? 2 pts 4. What is the probability of getting a sum of 13 or more?
Mathematics
1 answer:
bezimeni [28]2 years ago
8 0

Given:

Two dice are rolled together.

Total number of possible outcomes.

To find:

The list of total possible outcomes.

The probability of getting a sum of 11 in these outcomes.

The probability of getting a sum less than or equal to 4.

The probability of getting a sum of 13 or more.

Solution:

If two dice are rolled together, then the total number of possible outcomes is 36 and list of total possible outcomes is

S = {(1,1),(1,2),(1,3),(1,4),(1,5),(1,6),(2,1),(2,2),(2,3),(2,4),(2,5),(2,6),(3,1),(3,2),(3,3),(3,4),(3,5),(3,6),(4,1),(4,2),(4,3),(4,4),(4,5),(4,6),(5,1),(5,2),(5,3),(5,4),(5,5),(5,6),(6,1),(6,2),(6,3),(6,4),(6,5),(6,6)}

Sum of 11 in these outcomes = {(5,6),(6,5),(6,6)} = 3

The probability of getting a sum of 11 in these outcomes is

P(\text{sum=11})=\dfrac{3}{36}

P(\text{sum=11})=\dfrac{1}{12}

Therefore, the probability of getting a sum of 11 in these outcomes is \dfrac{1}{12}.

Sum less than or equal to 4 = {(1,1),(1,2),(1,3),(2,1),(2,2),(3,1)} = 6

The probability of getting a sum less than or equal to 4 is

P({sum\leq 4})=\dfrac{6}{36}

P({sum\leq 4})=\dfrac{1}{6}

Therefore, the probability of getting a sum less than or equal to 4 is \dfrac{1}{6}.

Sum of 13 or more = empty set because maximum sum is 12.

The probability of getting a sum of 13 or more is

P(sum\geq 13)=\dfrac{0}{36}

P({sum\geq 13})=0

Therefore, the probability of getting a sum of 13 or more is 0.

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Answer:

C. 22

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Inverse Alternate Interior Angles Theorem sttes that if two lines a and b are cut by transversal f so that the alternate interior angles are congruent, then a║b.

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6x-36=96\\ \\6x=96+36\\ \\6x=132\\ \\x=22

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A recent nationwide study investigated the value of the prostate-specific antigen (PSA) blood test for the detection of prostate
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Step-by-step explanation:

Remember:

Any medical test used to detect certain sicknesses have several probabilities associated with their results.

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True positive (test is + and the patient is sick) ⇒ P(+ ∩ S)

False-positive (test is + but the patient is healthy) ⇒P(+ ∩ H)

Negative (test is -) ⇒ P(-)

True negative (test is - and the patient is healthy) ⇒ P(- ∩ H)

False-negative (test is - but the patient is sick) ⇒ P(- ∩ S)

You can arrange them in a contingency table as:

Probabilities  Positive ; Negative

           Sick     + ∩ S    ;    - ∩ S        S          

      Healthy    + ∩ H    ;   - ∩ H        H

                            +              -            1

The sensibility of the test is defined as the capacity of the test to detect the sickness in sick patients (true positive rate).

⇒ P(+/S) = <u>P(+ ∩ S)</u>

                    P(S)

The specificity of the test is the capacity of the test to have a negative result when the patients are truly healthy (true negative rate)

⇒ P(-/H) = <u>P(- ∩ H)</u>

                    P(H)

1) You are studying the value of the prostate-specific antigen (PSA) blood test for the detection of prostate cancer on men of 50 years of age and older.

Total 100000 men

686 men tested positive

281 of the men that tested positive had cancer

45 men that tested negative had cancer

Total - positive cases: 100000 - 686 = 99314 tested negative

              ;  Positive   ;   Negative   ;   Total

Sick        ;     281       ;      45           ;    326

Healthy  ;     405      ;    99269      ;   99674

Total       ;    686       ;    99314       ;  100000  

2)

Sensitivity of the test is

P(+/S) = <u>P(+ ∩ S) </u>=  <u>0.00281 </u>= 0.86

                P(S)        0.00326

Where:

P(+ ∩ S) = 281/100000 = 0.00281

P(S) = 326/100000 = 0.00326

The test has an 86% probability of detecting PSA in sick patients.

3)

Specificity of the test is

P(-/H) = <u>P(- ∩ H) </u>= <u>0.99269 </u>= 0.995

                P(H)       0.99674

Where:

P(- ∩ H)= 99269/100000= 0.99269

P(H)= 99674/100000= 0.99674

The test has a 99.5% probability of not detecting PSA in healthy patients.

4)

Positive predictive value (PPV)

It's defined as the probability of being sick when the test is positive:

P(S/+)= <u>P(S ∩ +) </u>= <u>0.00281 </u>= 0.04

                P(+)       0.0686

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P(+)= 686/100000= 0.0686

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5)

Negative predictive value (NPV)

P(H/-)= <u>P(H ∩ -) </u>= <u>0.99269 =</u> 0.999

               P(-)        0.99314

Where:

P(-)= 99314/100000= 0.99314

There is a 99.9% probability of being healthy if the test is negative.

6 to 10 are all examples of medical tests.

I hope this helps!

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