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Question 1 of 10
1. Question
A continuous random variable can take on any value within a given range. Which of the following is an example of a continuous random variable?
I. The return of a stock index
II. Economy
III. Sales
IV. The prices of inflationCorrect
A continuous random variable can take on any value within a given range. A good example of a continuous random variable is the return of a stock index.
Incorrect
A continuous random variable can take on any value within a given range. A good example of a continuous random variable is the return of a stock index.

Question 2 of 10
2. Question
If the level of the index can be any real number between zero and infinity, then the return of the index can be any real number that is?
I. lesser than 0.
II. greater than 0.
III. lesser than 1.
IV. greater than –1.Correct
If the level of the index can be any real number between zero and infinity, then the return of the index can be any real number greater than –1.
Incorrect
If the level of the index can be any real number between zero and infinity, then the return of the index can be any real number greater than –1.

Question 3 of 10
3. Question
if the range that the continuous variable occupies is finite, the number of values that it can take is infinite. For this reason, for a continuous variable, the probability of any specific value occurring is?
I. finite
II. one
III. zero
IV. infiniteCorrect
Even if the range that the continuous variable occupies is finite, the number of values that it can take is infinite. For this reason, for a continuous variable, the probability of any specific value occurring is zero.
Incorrect
Even if the range that the continuous variable occupies is finite, the number of values that it can take is infinite. For this reason, for a continuous variable, the probability of any specific value occurring is zero.

Question 4 of 10
4. Question
Calculate the probability that a stock return is either below –10 percent or above 10 percent, given:
P[R < −10%] = 14% P[R > +10%] = 17%I. 31%
II. 3%
III. 1.22%
IV. 238%Correct
Note that the two events are mutually exclusive; the return cannot be below –10 percent and above 10 percent at the same time. The answer is: 14 percent + 17 percent = 31 percent.
Incorrect
Note that the two events are mutually exclusive; the return cannot be below –10 percent and above 10 percent at the same time. The answer is: 14 percent + 17 percent = 31 percent.

Question 5 of 10
5. Question
According to the most recent weather forecast, there is a 20 percent chance of rain tomorrow. The probability that stock XYZ returns more than 5 percent on any given day is 40 percent. The two events are independent. What is the probability that it rains and stock XYZ returns more than 5 percent tomorrow?
I. 10%
II. 8%
III. 12&
IV. 37&Correct
Since the two events are independent, the probability that it rains and stock XYZ returns more than 5 percent is just the product of the two probabilities. The answer is: 20 percent × 40 percent = 8 percent.
Incorrect
Since the two events are independent, the probability that it rains and stock XYZ returns more than 5 percent is just the product of the two probabilities. The answer is: 20 percent × 40 percent = 8 percent.

Question 6 of 10
6. Question
In regards to probability, when two coins are tossed, what is the probability that two heads are obtained?
I. 25%
II. 50%
III. 75%
IV. 85%Correct
The sample space D is given by.
D = {(H,T),(H,H),(T,H),(T,T)}
Let F be the event “two heads are obtained”.
F = {(H,H)}
We use the formula of the classical probability.
P(F) = n(F) / n(D) = 1 / 4 = 25%
Incorrect
The sample space D is given by.
D = {(H,T),(H,H),(T,H),(T,T)}
Let F be the event “two heads are obtained”.
F = {(H,H)}
We use the formula of the classical probability.
P(F) = n(F) / n(D) = 1 / 4 = 25%

Question 7 of 10
7. Question
A die is rolled and a coin is tossed, find the probability that the die shows an odd number and the coin shows a head.
I. 3/12
II. 1/4
III. 7/12
IV. 1/2Correct
The sample space S of the experiment described in question 5 is as follows
S = { (1,H),(2,H),(3,H),(4,H),(5,H),(6,H)
(1,T),(2,T),(3,T),(4,T),(5,T),(6,T)}Let E be the event “the die shows an odd number and the coin shows a head”. Event E may be described as follows
E={(1,H),(3,H),(5,H)}
The probability P(E) is given by
P(E) = n(E) / n(S) = 3 / 12 = 1 / 4
Incorrect
The sample space S of the experiment described in question 5 is as follows
S = { (1,H),(2,H),(3,H),(4,H),(5,H),(6,H)
(1,T),(2,T),(3,T),(4,T),(5,T),(6,T)}Let E be the event “the die shows an odd number and the coin shows a head”. Event E may be described as follows
E={(1,H),(3,H),(5,H)}
The probability P(E) is given by
P(E) = n(E) / n(S) = 3 / 12 = 1 / 4

Question 8 of 10
8. Question
The blood groups of 200 people is distributed as follows: 50 have type A blood, 65 have B blood type, 70 have O blood type and 15 have type AB blood. If a person from this group is selected at random, what is the probability that this person has O blood type?
I. 10%
II. .05%
III. .35%
IV. 35%Correct
We construct a table of frequencies for the the blood groups as follows
group frequency
a 50
B 65
O 70
AB 15We use the empirical formula of the probability
Frequency for O blood
P(E)= ________________________________________________
Total frequencies= 70 / 200 = 0.35
Incorrect
We construct a table of frequencies for the the blood groups as follows
group frequency
a 50
B 65
O 70
AB 15We use the empirical formula of the probability
Frequency for O blood
P(E)= ________________________________________________
Total frequencies= 70 / 200 = 0.35

Question 9 of 10
9. Question
One attribute that makes log returns particularly attractive is that they can be modeled using which of the following?
I. present value algorithms
II. probabilities
III. normal distributions
IV. statisticsCorrect
One attribute that makes log returns particularly attractive is that they can be modeled using normal distributions.
Incorrect
One attribute that makes log returns particularly attractive is that they can be modeled using normal distributions.

Question 10 of 10
10. Question
The normal distribution is often referred to as which of the following because of the shape of its probability density function?
I. the wave
II. the spiral
III. the diamond
IV. the bell curveCorrect
The normal distribution is often referred to as the bell curve because of the shape of its probability density function
Incorrect
The normal distribution is often referred to as the bell curve because of the shape of its probability density function