1.https://www.youtube.com/watch?v=Cl8zetzDBfM.post your comments how the present

Question

1.https://www.youtube.com/watch?v=Cl8zetzDBfM.post your comments how the presentation affects your view of making sense out of numbers and data.
2.

Linear Regression 5.1 For the following set of data, 19 10 20 14 4 Compute the Pearson correlation. Determine if there is a relationship, what type of relationship, and how strong or weak that relationship is, if any relationship exists. a. b. Find the linear regression equation for predicting Y from X (use the linear c. Use the regression equation that you derived (part b above) to compute the regression equation formula #1 from class handout). predicted Y for each actual value of X. Compare the predicted Y scores to the actual Y scores. Why is there a difference between the predictedY values and the actual Y values? How do you explain this difference?

Explanation / Answer

1. Answer

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The golden rule says, " Correlation DOES NOT imply causation ". This means, that two things can be highly correlated, but that doesn't mean that one is the cause of other or vice versa.

However,

Unfortunately, intuition can lead us astray when it comes to distinguishing between the two. For example, eating breakfast has long been correlated with success in school for elementary school children. It would be easy to conclude that eating breakfast causes students to be better learners. Is this a causal relationship—does breakfast by itself create better students? Or is it only a correlation: perhaps not having breakfast correlates highly with other challenges in kids’ lives that make them poorer students, such as less educated parents, worse socio-economic status, less focus on school at home, and lower expectations.

It turns out that kids who don’t eat breakfast are also more likely to be absent or tardy—and absenteeism plays a significant role in their poor performance. This may lead one to believe that there is not a causal relationship. Yet breakfast may encourage kids to come to school (and on-time), which then improves their performance in school, and so perhaps encourages attendance, which then results in better performance.

Thus,

the above video makes is clear that causation and correlation must be clearly defined in the context and one must not jump to conclusions about correlation implying causation.

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