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What is Central Tendency – An Introduction to Mean, Median, and Mode in Statistics (5-1) - YouTube
Channel: Research By Design
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Hi, I'm Dr. Todd Daniel and you're
watching Statistics for the Flipped
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Classroom. Last time, I showed you how to
display data with pictures. Now, I'm going
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to teach you how to display your data
with numbers. There are some specific
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numbers that we want to know about our
data, and foremost we want to know where
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is the center of the data. There are
three ways that we can describe central
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tendency: mean, median, and mode. I'm going to teach you when we will use each
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measure of central tendency, and how to
compute each one.
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Let's get started.
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We have two important questions about
our data set. The first question is; what
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single number best represents our data?
Our second question is whether the
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scores are packed together or spread out.
The answer to our first question about
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the most representative score is going
to be some measure of central tendency.
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A measure of central tendency indicates
where the center or the middle of the
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distribution tends to be. So you took a
test, and you got 94%.
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You may have done exceptionally well,
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or maybe not. Perhaps you're really smart
or perhaps the test was really easy.
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If I just tell you the raw scores; 80,
94, 73, 88, 86, 72, then you still don't really
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know that much, but if you know that you
scored 94 and the class average was 80.5
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then you know that you did really well.
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A measure of central tendency answers
the question of whether the scores are
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generally high or generally low. For
example, if I tell you about my friend
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who is a basketball player,
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what do you assume about his height?
Based on what you know about basketball
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players in general, you might assume that his height is above average because you
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know that the height of basketball
players is generally high. If I tell you
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about my friend who is a horse jockey,
you might assume that his height is
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generally low. These estimates are based
on what you already know about what the
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heights of certain individuals tend to
be. You are using a measure of central
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tendency. Measures of central tendency
offer the benefit of simplification.
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The whole sample of raw data is difficult to understand. A measure of central tendency
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gives us a single number that represents
the entire data set. Central tendency
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also has the benefit of prediction.
Knowing a measure of central tendency
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can help us to predict other scores
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or estimate future needs and this is
true even if the measure of central
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tendency is not in the actual data set.
If I tell you that the average family
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has 2.3 children, but that our city is
projected to grow by 1,000 families in
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the next five years, how many new
classroom seats will we need in public
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schools? Although no family who moves to our town literally has 2.3 children, that
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average is still very useful for
predicting how many children will be
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entering the school system. Determining
which measure of central tendency to use
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depends upon two things.
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First, it depends upon the scale of measurement; nominal, ordinal, interval, or ratio.
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For instance, the mean is typically used with interval or ratio level data. Second, our
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choice of a measure of central tendency
depends upon the shape of the
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distribution. If the distribution is
highly skewed or kurtotic, we may choose a
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specific measure of central tendency.
There are three measures of central
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tendency that we will learn about; mean,
median, and mode.
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