# PSYC 210 Chapter Notes -Type I And Type Ii Errors, Statistical Power, Null Hypothesis

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Published on 14 Oct 2012
School
Simon Fraser University
Department
Psychology
Course
PSYC 210
Chapter 6 Vocabulary 1
Decision errors incorrect conclusion in hypothesis testing in relation to the real but unknown situation despite
doing the correct calculations and steps
Type I error alpha () rejecting the null hypothesis when in fact it is true; getting a statistically
significant result when in fact the research hypothesis is not true
Type II error beta () failing to reject the null hypothesis when in fact it is false; failing to get a
statistically significant result when in fact the research hypothesis is true
---------------------------DECISION ERRORS---------------------------
Real Situation (in practice, unknown)
Null Hypothesis True
Research Hypothesis True
Conclusion Using
Hypothesis-Testing
Procedure
Research hypothesis
supported (reject null)
Type I error -
Correct decision
Study is inconclusive (do not
reject null)
Correct decision
Type II error -
Effect size () in studies involving means of one or two groups, measure of difference (lack of overlap) between
populations; the usual standardized effect size measure increases with greater differences between means and
decreases with greater standard deviations in the population, but isn’t affected by sample size; the difference
between the population means divided by the population’s standard deviation
    
Effect size conventions standard rules about what to consider a small, medium, and large effect size, based on
what is typical in psychology research; also known as Cohen’s conventions
Description
Effect Size 
Small
.20
Medium
.50
Large
.80
Meta-analysis statistical method for combining effect sizes from different studies
Statistical power probability that a study will give a significant result if the research hypothesis is true
* INFLUENCES ON POWER *
Increases Power
Decreases Power
Large d
Small d
Large differences
Small differences
Small δ
Large δ
Large N
Small N
Lenient, high (.05 or .10)
Extreme, low (.01 or .001)
One-tailed
Two-tailed
Varies
Varies
Power table table for a hypothesis-testing procedure showing the statistical power of studies with various effect
sizes and sample sizes
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## Document Summary

Decision errors incorrect conclusion in hypothesis testing in relation to the real but unknown situation despite doing the correct calculations and steps. Type i error alpha ( ) rejecting the null hypothesis when in fact it is true; getting a statistically significant result when in fact the research hypothesis is not true. Type ii error beta ( ) failing to reject the null hypothesis when in fact it is false; failing to get a statistically significant result when in fact the research hypothesis is true. Effect size conventions standard rules about what to consider a small, medium, and large effect size, based on what is typical in psychology research; also known as cohen"s conventions. Meta-analysis statistical method for combining effect sizes from different studies. Statistical power probability that a study will give a significant result if the research hypothesis is true. Effect size (d) (d = [ 1 - 2]/ ) Predicted difference between population means ( 1 - 2)