Bias and Validity in Research

Bias

Definition of Bias
- “A bias is a strong, preconceived notion of someone or something, based on information we have, perceive to have, or lack.”
- Involves subjective thinking and is influenced by personal perception or points of view.
- There are various types of bias; they are not universally detrimental.

Steps to Address Bias
1. Step 1: Be aware of different forms of bias.
2. Step 2: Learn different ways to mitigate bias.
3. Step 3: Appraise your own thinking, and reflect on where you might be taking short-cuts in your reasoning.

Example 1: Statement by the Coca-Cola Corporation: “Excess sugar intake won’t give you diabetes.”
Example 2: Statement by Biogen Pharmaceuticals: “This new drug will cure Alzheimer’s Disease.”
Importance of maintaining a balance in perception: Allow yourself to be both optimistic and skeptical regarding claims.

Key Concepts:
- Population: Entire group from which a sample is drawn.
- Sample: A subset of the population.
- Representative Sample: A sample that accurately reflects the characteristics of the population as a whole.
Types of Bias Associated with Sampling:
- Sample Bias: Occurs when the selected sample does not accurately represent the population of interest.
- Considerations:
- Always scrutinize who is being studied.
- Understand that clinic findings may not represent all clinics or populations.

Internal Validity:
- Defined as “How well the study is conducted.”
- Means that conclusions drawn from the study are warranted; it employs controls for confounding variables and eliminates alternate explanations.
External Validity:
- Defined as “How applicable are the findings to the real world?”
- Involves the ability to generalize findings; the results must apply to practical situations and can be utilized in other contexts.

Midterms are Coming!
- An important reminder for upcoming assessments that may require understanding of the above concepts.