Stats 2 test

. An experiment consists of four outcomes with P(E1) = 0.2, P(E2) = 0.3, and P(E3) = 0.4. The probability of outcome E4 is a. 0.500 b. 0.024 c. 0.100 d. 0.900

0.2+0.3+0.4+___=1 1-0.9=0.1 .100

6. If P(A) = 0.4, P(B | A) = 0.35, P(A∪B) = 0.69, then P(B) = a. 0.14 b. 0.43 c. 0.75 d. 0.59

0.43

Given that event E has a probability of 0.31, the probability of the complement of event E a. cannot be determined with the above information b. can have any value between zero and one c. 0.69 d. is 0.31

1 - .31=0.69

23. A continuous random variable is uniformly distributed between a and b. The probability density function between a and b is a. zero b. (a - b) c. (b - a) d. 1/(b - a)

1/(b-a)

5. Assuming that each of the 52 cards in an ordinary deck has a probability of 1/52 of being drawn, what is the probability of drawing a black ace? a. 1/52 b. 2/52 c. 3/52 d. 4/52

2/52

8. An experiment consists of three steps. There are four possible results on the first step, three possible results on the second step, and two possible results on the third step. The total number of experimental outcomes is a. 9 b. 14 c . 24 d. 36

4nPr3=24

22. Which of the following is not a characteristic of the normal probability distribution? a. symmetry b. The total area under the curve is always equal to 1. c. 99.72% of the time the random variable assumes a value within plus or minus 1 standard deviation of its mean d. The mean is equal to the median, which is also equal to the mode.

99.72% of the time the random variable assumes a value within plus or minus 1 standard deviation of its mean.

16. In the textile industry, a manufacturer is interested in the number of blemishes or flaws occurring in each 100 feet of material. The probability distribution that has the greatest chance of applying to this situation is the a. normal distribution b. binomial distribution c. Poisson distribution d. uniform distribution

Poisson distribution

20. The uniform, normal, and exponential distributions are a. all continuous probability distributions b. all discrete probability distributions c. can be either continuous or discrete, depending on the data d. all the same distributions

all continuous probability distributions

24. A continuous random variable may assume a. all values in an interval or collection of intervals b. only integer values in an interval or collection of intervals c. only fractional values in an interval or collection of intervals d. all the positive integer values in an interval

all values in an interval or collection of intervals

21. A value of 0.5 that is added and/or subtracted from a value of x when the continuous normal distribution is used to approximate the discrete binomial distribution is called a. 50% of the area under the normal curve b. continuity correction factor c. factor of conversion d. all of the alternatives are correct answers

continuity correction faction

14. An experiment consists of determining the speed of automobiles on a highway by the use of radar equipment. The random variable in this experiment is a a. discrete random variable b. continuous random variable c. complex random variable d. simplex random variable

continuous random variable

13. A random variable that can assume only a finite number of values is referred to as a(n) a. infinite sequence b. finite sequence c. discrete random variable d. discrete probability function

discrete random variable

12. Which of the following is a characteristic of an experiment where the binomial probability distribution is applicable? a. the experiment has at least two possible outcomes b. exactly two outcomes are possible on each trial c. the trials are dependent on each other d. the probabilities of the outcomes changes from one trial

exactly two outcomes are possible on each trial

15. When sampling without replacement, the probability of obtaining a certain sample is best given by a a. hypergeometric distribution b. binomial distribution c. Poisson distribution d. normal distribution

hypergeometric distribution

19. The center of a normal curve is a. always equal to zero b. is the mean of the distribution c. cannot be negative d. is the standard deviation

is the mean of the distribution

3. The intersection of two mutually exclusive events a. can be any value between 0 to 1 b. must always be equal to 1 c. must always be equal to 0 d. can be any positive value

must always be equal to 0

1.The counting rule that is used for counting the number of experimental outcomes when n objects are selected from a set of N objects where order of selection is important is called a. permutation b. combination c. multiple step experiment d. none of these alternatives is correct

permutation

2. A method of assigning probabilities based upon judgment is referred to as the a. relative method b. probability method c. classical method d. subjective method

subjective method

47. The multiplication law is potentially helpful when we are interested in computing the probability of a. mutually exclusive events b. the intersection of two events c. the union of two events d. conditional events

the intersection of two events

9. Bayes' theorem is used to compute a. the prior probabilities b. the union of events c. intersection of events d. the posterior probabilities

the posterior probabilities

18. For a normal distribution, a positive value of z indicates that a. all the observations must have had positive values b. the area corresponding to the z is either positive or negative c. the sample mean is smaller than the population mean d. the sample mean is larger than the population mean

the sample mean is larger than the population mean

17. Which of the following is not a characteristic of an experiment where the binomial probability distribution is applicable? a. the experiment has a sequence of n identical trials b. exactly two outcomes are possible on each trial c. the trials are dependent d. the probabilities of the outcomes do not change from one trial to another

the trials are dependent

4. The addition law is potentially helpful when we are interested in computing the probability of a. independent events b. the intersection of two events c. the union of two events d. conditional events

the union of two events