Deck 6: Curves and Distributions

Question 1

The approximate percentage of cases between the mean and negative one standard deviation (-1 s)in a normal curve is:

A) 34%
B) 68%
C) 95%
D) 47.5%

Answer 1

A

Question 2

In a normal curve, the lowest probability of a score occurring would be found at the end of the curve.

Answer 2

False

Question 3

The shape of a variable is referred to as its

A) internal variance
B) parabolic function
C) distance function
D) distribution

Answer 3

D

Question 4

Which of the following represent the concept of skewness?

A) the degree of peakedness of a curve
B) tails that never touch the baseline of a distribution
C) a lack of symmetry in the curve
D) a uniform area under the curve within ± 1 standard deviation

Question 5

Scores between the ends and the peak of a normal curve have an increasing probability of occurring as the point on the curve moves toward the peak.

Question 6

If a curve is asymptotic, it means that

A) the middle of the curve will never touch the baseline
B) the ends of the curve will never touch the baseline
C) both ends of the curve are identical
D) the scores in the curve increase until they reach infinity

Question 7

One way of determining that a curve may differ from the normal curve is called

A) kurtosis
B) a differencing technique
C) nonnormal variance
D) the coefficient of normality

Question 8

As long as you have a large enough sample, a random sampling process is not necessary in order to assume a normal curve.

Question 9

The peak of a normal curve has

A) some of the lowest scores in the distribution
B) the highest probability of a score occurring
C) a relationship to the baseline such that the square of the peak is proportional to the cube of the tails
D) no relationship to the baseline

Question 10

If a variable is normally distributed, it would have approximately:

A) 95 percent of the cases within 1 standard deviation around the mean
B) 47.5 percent of the cases between the mean and +2 standard deviations
C) 68 percent of the cases within 2 standard deviations around the mean
D) 68 percent of the cases between the mean and -1 standard deviation

Question 11

A symmetrical curve means that a symbolic measurement has been used.

Question 12

Each distribution has at least three important parts. They are

A) the elements, the labels, and the data
B) the mean, the standard deviation and the skewness
C) the peak, the mean, and the median
D) the peak, the baseline, and the tails

Question 13

If the mean of a distribution is assigned the value of zero, then all scores above the mean would be negative numbers.

Question 14

Two reasons we can be assured that a normal distribution is a reasonable assumption for many variables are:

A) the Centrality Theorem and Thompson's Limited Tails Theorem
B) the Inequality Theorem and the Reasonably Normal Theorem
C) Tchebychev's Inequality Theorem and the Central Limit Theorem
D) none of the above

Question 15

Every type of curve actually represents a probability distribution.

Question 16

Z-scores are used to describe the relative position of a mean.

Question 17

Another name for a normal curve is the unique normal distribution.

Question 18

A mean of 10 and a standard deviation of 5 would result in a standard score of

A) 50
B) 0.5
C) 2.0
D) there is not enough information to calculate a standard score

Question 19

When the normal curve is paired with the standard deviation, a fixed set of point emerges that

A) provide us with probabilities of a score occurring
B) can be used with Z-scores to determine the probability of kurtosis occurring
C) provide a unique assessment of probability in comparison to uniform distributions
D) all of the above

Question 20

A normal distribution (the theoretical concept) will be:

A) 68 percent of all cases located at the ends of the curve
B) asymptotic
C) symmetrical
D) b and c above

Question 21

A uniform distribution has a uniformly increasing number of scores throughout the curve.

Question 22

At ±3 s more than 99% of all scores are accounted for.