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A Few Words on Statistics
© Kim Taylor, September 2007
If you plan to major in the social sciences or some other programs, you’ll take at
least one entire course in statistics. As most of you haven’t selected that college
path (just wait ‘til you finish this course…. you’ll be itching to go into
psychology…), I’ll go easy on you here.
Regardless of your major or career field, it’s important to have an elementary
understanding of “stats”. I’m not going to throw formulas your way; rather I’ll
gently toss you a few terms that you’ll likely hear (and should know).
Ready? Get in position. Here they come. (Trust me… this will be painless as long
as you pay attention.)
Descriptive statistics – calculations and measures used to “describe” your data
Inferential statistics – calculations and measures used to “infer” conclusions
about your data
Three types of measures are used to describe performance in a group of scores:
shape of the distribution, measures of central tendency and measures of
variability.
Shape of the distribution – is the bell curve symmetrical, positively skewed or
negatively skewed?
Measures of central tendency – values (numbers) that reflect the middle or
central points of a group of scores
The three most used measures of central tendency are the:
Mean – the average of a set of scores (sum of numbers divided by the
number of numbers).
Median – the midpoint of a set of scores (the same number of scores are
both above and below the median). What if there is an even number of
scores? How do you determine the median then?
Mode – the most frequently occurring value in a set of scores. What term
is used to describe a distribution in which two values occur the same
number of times?
Use the following scores and calculate the measures of central tendency:
6, 10, 12, 8, 5, 7, 6, 9, 5, 7
Mean =
Median =
Mode =
Note: In a symmetrical bell curve, the mean, median and mode are the same
number.
Measures of variability – values that reflect the spread or dispersion of scores
Three measures of variability include the:
Range – simply the largest score minus the smallest score. What is the
range for the distribution of numbers above?
Variance – how possible scores are spread around an expected score
Standard deviation – average dispersion in a set of scores
Two more terms…. You’re almost finished….
Percentile – on a scale of 100, a value that represents the percent of scores that
is equal to or below it. So, what does it mean to say that Susie scored at the 80th
percentile on the SAT?
Statistical significance – a measure of the probability that the dependent variable
(DV) is the result of manipulation of the independent variable (IV) and not due
to chance
You can stop holding your breath now… we’re finished with statistics.