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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.