Chapter 3 Flashcards

1
Q

what are frequency distribs useful for? what is a main advntage of using f using frequency distributions or graphs is to summarize quantitative
information

A

Frequency distributions and graphical techniques are useful tools for describing data. The
main advantage of using frequency distributions or graphs is to summarize quantitative
information in ways that can be easily understood even by a lay audience

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2
Q

Measures of central tendency

A

y Categories or scores that describe what is average or typical of the
distribution.

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3
Q

We will see that the choice of an appropriate measure of central tendency for representing a
distribution depends on three factors:

A

(1) the way the variables are measured (their level of

measurement) , (2) the shape of the distribution, and (3) the purpose of the research.

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4
Q

mode and what level of measurement is it used in

A

The mode is the category or score with the largest frequency or percentage in the
distributionThe mode is the only measure of central tendency that can be used with nominal-level
variables

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5
Q

what is the mode - a category/score or a frequency?

A

a category/score, The mode
is not necessarily the category with the majority (i.e., more than 50%) of cases, as it is in
Table 3.1; it is simply the category in which the largest number (or proportion) of cases fall

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6
Q

why is the mode the only measure of CT to be used with nominal level vbles

A

Recall that with nominal variables—such as foreign languages spoken in the
United States, race/ethnicity, or religious affiliation—we are only able to classify
respondents based on a qualitative and not on a quantitative property. However, the mode
can also be used to describe the most commonly occurring category in any distribution

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7
Q

what is bimodal? what should you report in these situations?

A

When two
scores or categories with the highest frequencies are quite close (but not identical) in
frequency, the distribution is still “essentially” bimodal. In these situations, you should not
rely on merely reporting the (true) mode, but instead report the two highest frequency
categories.

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8
Q

median

A

The score that divides the distribution into two equal parts so that half the cases are above it and
half below it.

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9
Q

what does the median represent

A

the exact middle of a
distribution; it is the score that divides the distribution into two equal parts so that half the
cases are above it and half below it.

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10
Q

The median is a suitable measure for those variables whose

A

categories or scores can be arranged in order of magnitude from the lowest to the highest.

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11
Q

what happens with a median (for ex, for the fair example on pgs 132-133)

A

Notice that the median divides the distribution exactly into
half so that there are two respondents who are more satisfied and two respondents who are
less satisfied.

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12
Q

what happens when data is ordinal

A

As a note of caution, when data are ordinal, averaging the middle two scores is no longer
appropriate. The median simply falls between two middle values.

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13
Q

how to find the median? what is it always?

A

To find the median, we need to identify the category associated with the observation
located at the middle of the distribution. This may seem odd; however, the median is always the
value of the response category, not the frequency.

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14
Q

We can also locate the median in a frequency distribution by using the cumulative
percentages column - how?

A

To find
the median, we identify the response category that contains a cumulative percentage value
equal to 50%. The median is the value of the category associated with this observation.

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15
Q

how to find the percentage value = to 50%?

A

If you are not sure
why the middle of the distribution—the 50% point—is associated with the category
“moderate,” look again at the cumulative percentage column (C%). Notice that 33% of the
observations are accumulated below the category “moderate” and that 66% are
accumulated up to and including the category “moderate.” We know, then, that the
percentage value equal to 50% is located somewhere within the “moderate” category.

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16
Q

what is a percentile? how is it connected to a median?

A

The median is a special case of a more general set of measures of location called percentiles.
A percentile is a score at or below which a specific percentage of the distribution falls

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17
Q

explain the 75th percentile

A

The
nth percentile is a score below which n% of the distribution falls. For example, the 75th
percentile is a score that divides the distribution so that 75% of the cases are below it

18
Q

like the median, what do percentiles requie? when are they easy to identify?

A

Like the median, percentiles require that data be ordinal or higher in
level of measurement. Percentiles are easy to identify when the data are arranged in
frequency distributions.

19
Q

explain how ACT percentiles work

A

e. Suppose for a moment that
90% of all students received a lower ACT score than you (and 10% scored above you).
Your percentile rank would have been 90

20
Q

what is a quartile? what is the lower and upper ones?

A

Another widely used measure of location is the quartile. The lower quartile is equal to the
25th percentile and the upper quartile is equal to the 75th percentile

21
Q

how would colleges calculate and use quartiles

A

A college admissions office interested in accepting the top
25% of its applicants based on their SAT scores could calculate the upper quartile (the 75th
percentile) and accept everyone whose score is equivalent to the 75th percentile or higher.
(Note that they would be calculating percentiles based on the scores of their applicants, not
of all students in the nation who took the SAT.)

22
Q

mean

A

A measure of central tendency that is obtained by adding up all the scores and dividing by the total
number of scores. It is the arithmetic average.

23
Q

formula

A

A formula is a shorthand way to explain what

operations we need to follow to obtain a certain result

24
Q

mean formula

A

y bar= (sigma y)/ N

25
Q

for the incarceration rate q on pg 142, wy select means?

A

Because the variable “incarceration rate” is an interval-ratio variable, we will select the
arithmetic mean as our measure of central tendency

26
Q

why is the mean the center of gravity of the distribution

A

Because the mean (unlike the mode and the median) incorporates all the scores in the
distribution, we can think of it as the center of gravity of the distribution. That is, the mean
is the point that perfectly balances all the scores in the distribution. If we subtract the mean
from each score and add up all the differences, the sum will always be zero!

27
Q

what is the difference between the mean versus the mode and median

A

unlike

with the mode or the median, every score enters into the calculation of the mean

28
Q

how are we investigating gender income inequality

A

gender income
equality has yet to be achieved. We continue our investigation of gender income inequality
by reviewing published income data.

29
Q

why may mean not be the best measure of central tendency for income? what is more commonly used?

A

, due to its sensitivity to extreme
values. median earnings. . We can use these medians to note the differences
between subgroups of the population or changes over time.

30
Q

what should you do when a researcher reports an avg score?

A

When mean income scores are reported, interpret with caution as extremely low or high
income values may skew the distribution. When a researcher reports an “average” score,
assess whether the calculation was based on a median or a mean.

31
Q

The distribution of interval-ratio variables can also be described by …

A

their general shape

32
Q

Using histograms, produced by SPSS, we will demonstrate how a distribution can be ….

A

either
symmetrical or skewed, depending on whether there are a few extreme values at one end of
the distribution

33
Q

symmetrical distribution

A

n The frequencies at the right and left tails of the distribution are identical; each
half of the distribution is the mirror image of the other.

34
Q

skewed distrib

A

n A distribution with a few extreme values on one side of the distribution.

35
Q

positvely skewed distrbution

A

A distribution with a few extremely high values. When the mean is higher than the median (or is positioned to the right of the
median), the distribution is positively skewed.

36
Q

negatively skewed distribution

A

A distribution with a few extremely low values. When the mean is lower than the median (or is positioned to the left of the median),
the distribution is negatively skewed.

37
Q

what is the main consideration in choosing a measure of central tendency

A

The variable’s level of measurement is the primary consideration in choosing a measure of
central tendency. The measure of central tendency should be appropriate to the level of
measurement. Thus, as shown in Figure 3.11, with nominal variables our choice is
restricted to the mode as a measure of central tendency.

38
Q

what measures of central tendency can we use with oridnal data

A

(1) the mode or (2) the median (or

sometimes both

39
Q

When the distribution is skewed, the mean may give 1 The 2 can be chosen as the preferred measure of central
tendency because neither is influenced by extreme scores.

A

1misleading information on the central
tendency because its value is affected by extreme scores in the distribution.

2median
or the mode

40
Q

what is the median calculated for

A

n. It is

often used to describe the most commonly occurring category of a nominal-level variable

41
Q

what happens with skewed distributions v symmetrical distributions

A

In a symmetrical distribution, the frequencies at the right and left tails of the distribution are
identical. In skewed distributions, there are either a few extremely high (positive skew) or a few
extremely low (negative skew) values