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Flashcards in Review: Normal Dist Deck (30):
1

The Empirical Rule of probability can be applied to the uniform probability distribution
T/F

FA

2

Areas within a continuous probability distribution represent probabilities.
T/F

TR

3

The total area within a continuous probability distribution is equal to 100.
T/F

FAL

4

The total area within any continuous probability distribution is equal to 1.00
T/F

TR

5

For any continuous probability distribution, the probability, P(x), of any value of the random variable, X, can be computed.
T/F

FA

6

For any discrete probability distribution, the probability, P(x), of any value of the random variable, X, can be computed.
T/F

TR

7

The uniform probability distribution's standard deviation is proportional to the distribution's range.
T/F

TR

8

For any uniform probability distribution, the mean and standard deviation can be computed by knowing the maximum and minimum values of the random variable.
T/F

T

9

In a uniform probability distribution, P(x) is constant between the distribution's minimum and maximum values.
T/F

TR

10

For a uniform probability distribution, the probability of any event is equal to 1/(b-a).
T/F

FA

11

The uniform probability distribution is symmetric about the mode.
T/F

FA

12

The uniform probability distribution's shape is a rectangle.

TR

13

The uniform probability distribution is symmetric about the mean and median.
T/F

T

14

A continuity correction factor compensates for estimating a discrete distribution with a continuous distribution

TR

15

When referring to the normal probability distribution, there is not just one; there is a "family" of distributions.

TR

16

The area under the normal curve within plus and minus one standard deviation of the mean is about 68.26%.

TR

17

The total area under the normal curve is 100%.

TR

18

The shape of any uniform probability distribution is
A) Negatively skewed
B) Positively skewed
C) Rectangular
D) Bell shaped

C

19

The upper and lower limits of a uniform probability distribution are
A) positive and negative infinity
B) plus and minus three standard deviations.
C) 0 and 1
D) the maximum and minimum values of the random variable.

D

20

When using the binomial distribution to approximate a normal distribution, what is the value of the continuity correction factor?
A) 1.00
B) 0.50
C) 100
D) 1.96

B

21

What is an important similarity between the uniform and normal probability distributions?
A) The mean, median and mode are all equal.
B) The mean and median are equal
C) They are negatively skewed
D) About 68% of all observations are within one standard deviation of the mean.

B

22

Which of the following is NOT true regarding the normal distribution?
A) Mean, median and mode are all equal
B) It has a single peak
C) It is symmetrical
D) The points of the curve meet the X-axis at z = –3 and z = 3

D

23

For the normal distribution, the mean plus and minus 1.96 standard deviations will include about what percent of the observations?
A) 50%
B) 99.7%
C) 95%
D) 68%

C

24

Which of the following is NOT a characteristic of the normal probability distribution?
A) Positively-skewed
B) Bell-shaped
C) Symmetrical
D) Asymptotic

A

25

Which of the following is true in a normal distribution?
A) Mean equals the mode and the median
B) Mode equals the median
C) Mean divides the distribution into two equal parts
D) All of the above are correct

D

26

Two normal distributions are compared. One has a mean of 10 and a standard deviation of 10. The second normal distribution has a mean of 10 and a standard deviation of 2. Which of the following it true?
A) the locations of the distributions are different
B) the distributions are from two different families
C) the dispersions of the distributions are different
D) the dispersions of the distributions are the same

C

27

An area of a normal probability distribution represents
A) a permutation
B) a combination
C) a likelihood
D) a shaded area

C

28

What is a graph of a normal probability distribution called? _________

normal curve

29

What type of probability distribution is the normal distribution? ______________

Continuous

30

One of the properties of the normal curve is that it gets closer to the horizontal axis, but never touches it. What is this property of the normal curve called? _________________

asymptotic