# Week 4 Hypothesis testing Construction

Information about Week 4 Hypothesis testing Construction

Published on February 1, 2008

Author: physioactive

Source: authorstream.com

Hypothesis Testing & Construction:  Hypothesis Testing & Construction Chee-Wee Tan P1112 What are hypotheses?:  What are hypotheses? Hypothesis testing – put forward a statement / question for testing whether its true. H1 – Experimental Hypothesis H0 – Null hypothesis What are hypotheses?:  What are hypotheses? H1 – Watching day-time TV increases a person’s boredom H0 – Watching day-time TV does not increase a person’s boredom. Why use the null hypothesis?:  Why use the null hypothesis? You can never prove a hypothesis but only disprove it. A scientific theory is falsifiable. Spot the Vulcan contest How to test a hypothesis?:  How to test a hypothesis? If probability of results happening by chance decreases, more confident of rejecting null hypothesis. Convention: if result happening by chance is less than 5%, reject null hypothesis. How to test a hypothesis? :  How to test a hypothesis? Steps: Construct null hypothesis and experimental hypothesis. Administer intervention to one of the groups with the other acting as control. Calculate the probability of an effect happening by chance. If less than 5%, reject null hypothesis. How to test a hypothesis:  How to test a hypothesis H0: Students with enforced laziness does not have worse exam grades than students without enforced laziness. Class Enforced Laziness Control Exams P =0.3 Compare Determining if samples are different:  Determining if samples are different Depends on: Research design Statistical test 2 types of variation Systematic Unsystematic Test statistic and variations:  Test statistic and variations Test statistic: number with known characteristic. Examples, t and F. Tests statistic = Systematic variance Unsystematic variance The larger the test statistic, the better. Two mistakes we must know:  Two mistakes we must know Effect No effect Effect No effect Findings Actual Type I & II errors:  Type I & II errors Type I error (α-level) Usually set at 0.05 Type II error (β-level) Maximum acceptable level = 0.2 Increasing α will decrease β, vice versa Where is my sweater? Effect size:  Effect size If an effect exists, doesn’t mean it’s important or meaningful. Need to find effect size – The magnitude of the effect Used in meta-analysis Statistics: d, r, q, g, h, w, f & f2 Summary:  Summary Hypothesis testing Null hypothesis How hypothesis testing works Test statistics & variations Type I & II errors Effect size Resistance is futile, assimilate knowledge

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