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NOTES FOR SUMMER STATISTICS INSTITUTE COURSE COMMON MISTAKES IN STATISTICS SPOTTING THEM AND AVOIDING THEM Day 3 Type I and II Errors Power and the File Drawer Problem MAY 22 - 25 2017 Instructor Mary Parker CONTENTS OF DAY 3 I. Catch-up and review from yesterday as needed II. Trade-Off between Type I and Type II errors III. Deciding what significance level to use V. Power of a statistical procedure Factors affecting power Significance level Sample size Variance Experimental design...
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Common mistakes in statistics include sampling errors, selection bias, and reliance on correlation to imply causation.
Researchers, statisticians, and analysts who are conducting studies or data analysis are required to be aware of common mistakes in statistics.
To avoid common mistakes in statistics, one should carefully plan the study design, use appropriate statistical methods, and critically evaluate the results.
The purpose of being aware of common mistakes in statistics is to ensure that data analysis is accurate and reliable, leading to sound conclusions and decision-making.
Information such as the study population, sampling method, statistical tests used, and interpretation of results must be reported to address common mistakes in statistics.
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