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Russel-Research-Method-in-Anthropology

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Univariate Analysis 563<br />

people hang<strong>in</strong>g around who aren’t old enough to leave and old people who<br />

can’t f<strong>in</strong>d work <strong>in</strong> the city because of their age.<br />

Us<strong>in</strong>g the Mode<br />

The mode is often said to be the weakest measure of central tendency, but<br />

it’s very useful when you want to make a statement about a prom<strong>in</strong>ent qualitative<br />

attribute of a group. ‘‘More people profess to be Buddhist <strong>in</strong> this prefecture<br />

of Japan than profess any other religion’’ is such a statement.<br />

The mode is also a good common-sense alternative to the sometimes unrealistic<br />

quality of the mean. Say<strong>in</strong>g that ‘‘the modal family size is 4 people’’<br />

makes a lot more sense than say<strong>in</strong>g that ‘‘the average family size is 3.81 people’’—even<br />

if both statements are true.<br />

You’ll often see the mode reported as a percentage: ‘‘In this survey, 60% of<br />

the respondents were men.’’<br />

The mode can also be reported <strong>in</strong> terms of ratios. Of the 30 respondents <strong>in</strong><br />

table 19.2, 12 were women and 18 were men, so the modal value for the variable<br />

GENDER <strong>in</strong> table 19.2 is male. The ratio of men to women among these<br />

respondents is 18/12 1.5, while the ratio of women to men is 12/18 .67.<br />

Report<strong>in</strong>g that ‘‘there were 1.5 men for every woman <strong>in</strong> this survey’’ is the<br />

same as say<strong>in</strong>g that ‘‘60% of the respondents were men.’’ Report<strong>in</strong>g that<br />

‘‘there were .67 women for every man <strong>in</strong> this survey’’ is the same as say<strong>in</strong>g<br />

that ‘‘40% of the respondents were women.’’<br />

Central Tendency: The Median<br />

The median is the po<strong>in</strong>t <strong>in</strong> a distribution above and below which there are<br />

an equal number of scores <strong>in</strong> a distribution. If you’ve ever taken a standardized<br />

test like the ACT, SAT, or GRE, you might have been told that you scored<br />

<strong>in</strong> the 14th percentile, or the 31st percentile, or whatever. If you scored <strong>in</strong> the<br />

86th percentile, then 14% of the scores were higher than yours (.86 .14 <br />

1.0).<br />

Ten percent of scores <strong>in</strong> a list are below the 10th percentile, and 90% are<br />

above it. The 25th percentile is called the first quartile and the 75th percentile<br />

is the third quartile. The difference between the values for the 25th and 75th<br />

percentiles is known as the <strong>in</strong>terquartile range and is a measure of dispersion<br />

for ord<strong>in</strong>al and <strong>in</strong>terval-level variables. (More on measures of dispersion<br />

later.)<br />

The median is the 50th percentile. It can be used with ranked or ord<strong>in</strong>al<br />

data and with <strong>in</strong>terval- or ratio-level data. For an odd number of unique obser-

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