PSYC 2030 Lecture Notes - Lecture 6: Presumption Of Innocence, Statistical Significance

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29 May 2018

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PSYC 2030 Lecture 6 Notes

Introduction

Test of Aggression

• Perhaps ou’e opared e’s ad oe’s sores o a laorator test of aggressio,

and found a gender difference.

• But individuals differ.

• How likely is it that the difference you observed was just a fluke?

• Statistical testing can estimate that.

• Here is the underlying logic

• When averages from two samples are each reliable measures of their respective

populations (as when each is based on many observations that have small variability),

then their difference is likely to be reliable as well.

• Eaple: The less the ariailit i oe’s ad i e’s aggressio sores, the ore

confidence we would have that any observed gender difference is reliable

• And when the difference between the sample averages is large, we have even more

confidence that the difference between them reflects a real difference in their

populations.

• In short, when sample averages are reliable, and when the difference between them is

relatively large, we say the difference has statistical significance.

• This means that the observed difference is probably not due to chance variation

between the samples.

• In judging statistical significance, psychologists are conservative.

• They are like juries who must presume innocence until guilt is proven.

• For most psychologists, proof beyond a reasonable doubt means not making much of a

finding unless the odds of its occurring by chance, if no real effect exists, are less than 5

percent.

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