Statistics 2037 - Chapter 11 Relationships Can Be Deceiving.docx

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Department
Statistical Sciences
Course
Statistical Sciences 2037A/B
Professor
Emad Mohammad
Semester
Fall

Description
Chapter 11 – Relationships Can Be Deceiving Correlation does not provide the complete picture. Many things can cause correlation. Others can inflate and deflate correlations. Groups combined inappropriately can mask relationships. Small samples are highly affected by outliers. Consistent outliers inflate the correlation, inconsistent outliers deflate it. Researchers usually check for initially recorded outliers. Outliers can occur as legitimate data. Some researchers may leave them in to lead you astray. Illegitimate correlation can occur when two or more groups are combined when they should be considered separately. Example: hardcover and soft cover books in price/page study. Together it is negative correlation, separately they are positive correlation. Correlation does not imply causation. Relationships and correlations from observed studies are reported as causal. Sometimes connections do make sense, but if there is no evidence we can’t prove causation. Some reasons that variables can be related include: The explanatory variable is a direct cause of the response variable. Even though they are related there may not be a strong association between the two variables. The response variable is causing a change in the explanatory variable. Causal connections can be opposite. Example: decrease in occupancy in a hotel means an increase in advertising.
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