Chapter 5 Flashcards

1
Q

The distributions that we have described so far are all empirical distributions—
that is, they are all based on

A

real data

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2
Q

The value of the theoretical normal

distribution lies in the fact that

A

t many empirical distributions that we study seem to
approximate it. t. We can often learn a lot about the characteristics of these empirical
distributions based on our knowledge of the theoretical normal distribution.

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3
Q

Normal distribution

A

n A bell-shaped and symmetrical theoretical distribution with the mean, the median,
and the mode all coinciding at its peak and with the frequencies gradually decreasing at both ends of the
curve.

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4
Q

what percent between mean and 1+, 2+ and 3+ resppectively

A

between the
mean and ±1 standard deviation, 68.26% of all the observations in the distribution occur;
between the mean and ±2 standard deviations, 95.46% of all observations in the
distribution occur; and between the mean and ±3 standard deviations, 99.72% of the
observations occu

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5
Q

. When we say that a

variable is “normally distributed,” we mean that the graphic display will

A

reveal an
approximately bell-shaped and symmetrical distribution closely resembling the idealized
model shown in Figure 5.1. This property makes it possible for us to describe many
empirical distributions based on our knowledge of the normal curve

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6
Q

As long as a
distribution is normal and we know the mean and the standard deviation, we can
determine the

A

proportion or percentage of cases that fall between any score and the mean.

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7
Q

This property provides an important interpretation for the standard deviation of empirical
distributions that are approximately normal. For such distributions, when we know the
mean and the standard deviation, we can determine

A

the percentage or proportion of scores
that are within any distance, measured in standard deviation units, from that distribution’s
mean.

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8
Q

The fixed

relationship between the distance from the mean and the areas under the curve applies only

A

to distributions that are normal or approximately normal.

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9
Q

z scores- what are they used to show

A

We can express the difference between any score in a distribution and the mean in terms of
standard scores,

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10
Q

A standard (Z) score is

A

the number of standard

deviations that a given raw score (or the observed score) is above or below the mean

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11
Q

A raw

score can be transformed into a Z score to find

A

how many standard deviations it is above or

below the mean.

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12
Q

To transform a raw score into a Z score, we

A

divide the difference between the score and the

mean by the standard deviation.

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13
Q

A Z score allows us to represent

A

t a raw score in terms of its relationship to the mean and to
the standard deviation of the distribution

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14
Q

The larger the Z score,
236
the larger the difference between

A

the score and the mean.

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15
Q

Standard normal distribution

A

n A normal distribution represented in standard (Z) scores, with mean = 0 and
standard deviation = 1.

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16
Q

Standard normal table

A

A table showing the area (as a proportion, which can be translated into a percentage)
under the standard normal curve corresponding to any Z score or its fraction.

17
Q

We can also convert proportions or percentages into

A

z scores

18
Q

To determine the percentile rank of a raw score

requires

A

s transforming Z scores into proportions or percentages.

19
Q

Converting percentile ranks

to raw scores is based on

A

transforming proportions or percentages into Z scores. In the
following examples, we illustrate both procedures based on the SAT writing scores data.
(pg 248)

20
Q

The normal distribution is central to …

it also…

A

The normal distribution is central to the theory of inferential statistics. It also provides a model for
many empirical distributions that approximate normality

21
Q

In all normal or nearly normal curves, we find a

A

In all normal or nearly normal curves, we find a constant proportion of the area under the curve
lying between the mean and any given distance from the mean when measured in standard
deviation units.

22
Q

The standard normal distribution is …

The proportions corresponding to…

A

The standard normal distribution is a normal distribution represented in standard scores, or Z
scores, with mean = 0 and standard deviation = 1. Z scores express the number of standard
deviations that a given score is located above or below the mean. The proportions corresponding to
any Z score or its fraction are organized into a special table called the standard normal table