1 / 17

Understanding the Relationship Between Two Numerical Variables

This article explores the intricate relationships between numerical variables, focusing on the distinction between correlation and causation. Investigators often rely on anecdotal evidence and multiple observations to identify associations. While a scatterplot can visually demonstrate the connection between independent (X) and dependent (Y) variables, it is crucial to understand that correlation does not imply causation. Key factors for establishing causation include association, sequence of events, underlying mechanisms, and counterfactual analysis. This guide offers insights into analyzing and interpreting data effectively.

tarika
Download Presentation

Understanding the Relationship Between Two Numerical Variables

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Relationship between Two Numerical Variables By Farrokh Alemi, Ph.D.

  2. Relationships Investigators are often interested in relationship between variables

  3. Anecdotal Data Multiple observations needed

  4. Anecdotal Data I have smoked all my life and I do not have cancer

  5. Relationships

  6. Independent X & Y

  7. Explanatory Variable

  8. Association Is Not Causation

  9. Causation Requires: • Association • Sequence (causes preceded effects) • Mechanism • Counter factual (no effect when causes are absent)

  10. Causation Requires: • Association • Sequence (causes preceded effects) • Mechanism • Counter factual (no effect when causes are absent)

  11. Causation Requires: • Association • Sequence (causes preceded effects) • Mechanism • Counter factual (no effect when causes are absent)

  12. Causation Requires: • Association • Sequence (causes preceded effects) • Mechanism • Counter factual (no effect when causes are absent)

  13. Association Is Not Causation

  14. Take Home Message A Scatterplot can show the association between two variables

  15. Do one:

More Related