Description
This week's Introduction about ice cream sales and crime rates was an example of correlation being mistaken for causation. In this Discussion, you will identify and analyze a real-world correlation and decide whether it truly shows causation.
To prepare for this Discussion:
- Review the Concepts and Applications exercises on pages 319–320 of your text, where you will find several problems describing real-life examples of correlation and causation. Think about how you might respond to the questions posed.
- Think about what real-life situations you have noticed that might show a correlation between two things. Perhaps it's a relationship between two events you've observed. Or maybe you read online or in a newspaper that as one thing changes, so does another.
- Determine whether the correlation is positive or negative.
- Describe how someone might infer that one event "causes" the other.
- Decide if this causation is reasonable, or if there is another explanation for why the two events are correlated. How might you decide, using scientific methods, whether one variable actually causes the other to occur?
By Day 3
Post a 1- to 2-paragraph write-up including the following:
- Describe a correlation in your daily life.
- Using scientific methods, explain how you determined whether one variable causes the other to occur.
- In the example you chose, describe what factors you need to be aware of when trying to establish a causal relationship.
- Decide whether the scenario represents a case of positive or negative correlation, and explain your choice.
Be sure to support your ideas by connecting them to the week's Learning Resources or to something you have read, heard, seen, or experienced.
Explanation & Answer
Attached.
1
Running head. CORRELATIONS AND CAUSAL CONNECTIONS
Correlations and Causal Connections
Name
Institutional affiliation
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CORRELATIONS AND CAUSAL CONNECTIONS
All genuinely causal connections are statistical correlations in nature. However, the
converse is not true. Some of the correlations are just statistical with no causal connections at
all (Altman, 2015). In my life, I experienced a correlation-causation dilemma. As a soccer
player, ...
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