# 11.2 - o This is the difference between these statistics...

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Statistical Significance Statistical significance means that 95% of the time, we know that these results will come true o Based on overall size of sample o How many people are in each group o “every time you roll the dice, what is happening” o More than chance o Must be .05% or less to be statistically significant The lack of a statistical significance can be important o Ex. In a study of the way people read online news and paper news there proves to be no statistical significance, that is actually important because it shows there is no change between the two ways of gathering news Mean, Standard Deviation (SD) Measure of central tendencies Mean = average Analyze > Descriptive > Frequencies o Click statistics: mean, SD
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Unformatted text preview: o This is the difference between these statistics and just a headcount • Ex. Age o Average age of people in Athens would have a large SD because the range is so huge (from 0 to like 90) o Average age of UGA undergrads would have a really small SD because almost everyone is between 18-22 and that is such a small set T test • Parametric, one IV on two samples of people • Difference between two means • Analyze > Compare Means > Independent samples t test o Test: the mean you want to test o Grouping variable: the cells compared • T test = the difference between TWO means • Under T test, the significance is the second significance (the one inside the big t-test box)...
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## This note was uploaded on 03/17/2010 for the course ADPR 3510 taught by Professor Sweetser during the Fall '09 term at UGA.

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