This tutorial will discuss bias, specifically focusing on:
Most often research is done accurately and with integrity. People want to get the job done right. They want to get the answer correct. But sometimes there's something that happens systematically in the experiment or the study that limits the accurate representation of the population that you're going for.
Bias, in the statistics world, is systematically misrepresenting the population. The favoring of certain outcomes in a sample that limits our ability to draw conclusions about the population. The key word is systematically. It's not necessarily intentional. It could be intentional, but it doesn't have to be. A way of selecting the sample for your study such that the sample doesn't accurately reflect the population is called selection bias. It's not good, but sometimes it can't be avoided.
However, sometimes it can be avoided, but isn't. Publication bias occurs when researchers only want to publish only the most sensational findings or rather, only the positive ones. Only the results that people will want to read make it to people's eyeballs. People not wanting to read things that they've deemed boring is publication bias.
Oftentimes, people will behave differently if they know that they're under observation. They become a bit self-conscious when they are observed and want to do it “right”, so they act differently.
You are in charge of a weight loss study. One group is told to take a pill every day, and the other group also takes a pill, but it doesn't have any ingredient in it. You instruct them to not change their behavior.
You don’t want them changing the results by eating differently or exercising more.However, these people might change their behavior based on the fact that they know they're going to be weighed later.
This idea that people might change what they would normally do based on the fact they're under observation is a type of bias called the “Hawthorne Effect”.
Also something to consider is that this study was also based on participants volunteering their time to be a part of this study. What may happen, is that only people with a passion for losing weight may have signed up, which is participation bias. And furthermore, another issue may be that the participants tell you what they think you want to hear, which is response bias.
Bias has a problematic influence in many experiments and samples. Unfortunately,when bias exists, the results received are not generalizable to the population. They're not reliable.
It’s important to know that bias is not always intentional. It can be a systematic flaw in the sample or in the experiment, but it's not always on purpose. Selection bias happens when the sample is not truly representative of the population to which you want to generalize the information. Publication bias is when researchers publish only the information that they think people want people see. The Hawthorne Effect is a type of bias that happens when people act differently just knowing they are being observed.
Source: this work is adapted from sophia author jonathan osters.
The tendency for collected data to differ from what is expected in a systematic way. Biased data can often favor a specific group of those studied.
People have the tendency to change their behavior when they know they are being monitored.
Bias that occurs when a sample consists entirely of volunteers. People with strong opinions may be the only ones who volunteer.
The desire of researchers (and research publications) to only print the most sensational or interesting articles.
Bias that occurs when a respondent tells the interviewer "what they want to hear" or lies due to the sensitive nature of the question.
Selecting a sample in such a way that certain subsets of the population are systematically excluded.