Avoid gender bias in your paper by avoiding the use of gendered pronouns, such as "he" or "she." According to the Purdue University Online Writing Lab, you should not write "he or she," "he/she" or alternate between "he" and "she" in different paragraphs, as this becomes confusing for readers. To eliminate bias, rephrase sentences so that gendered pronouns can be replaced with gender-neutral nouns such as "people," "children," "scientists" and "individuals." For instance, rather than writing "businessmen study marketing" you could say "businesspeople study marketing."
Limit your use of biased labels to describe populations of people. This is especially true when dealing with sensitive issues people face, like disability or health conditions. Be aware that these people may not want to be called something in particular. The Purdue University Online Writing Lab (OWL) says that this approach to avoiding biased labels also applies to writing about sexuality, ethnicity or religion. For instance, rather than saying "People who are bipolar," the non-biased way to rephrase the clause is "People who are diagnosed with bipolar disorder." Or, "People of the Jewish faith believed..." is a non-biased alternative to saying "The Jews believed..." Being called "bipolar" or "a Jew" can be offensive because it implies that the person only exists within that classification, OWL argues. When you write "people who are diagnosed with bipolar disorder" you are acknowledging that the person has a condition, rather than implying that the person "is" the condition.
Focus on facts. Avoid adding your own opinion by manipulating the material to sound the way you want it to sound. For example, if a specific statistic says that 50 percent of people experience nightmares, you should not write "most people experience nightmares" simply to satisfy your argument that nightmares are common. Rather, to have a non-biased paper you would write the statistic the way it is. Data manipulation is an unethical way to represent data in your paper. A research paper is not about portraying your own agenda on the topic, but rather about supporting concepts and ideas relative to particular issues.
Provide a variety of samples in your research paper to avoid sampling bias. Sampling bias occurs when you use one type of research sample that only represents one set of data, excluding the rest in order to make an argument. For instance, according to the University of Wisconsin, if you write a paper about substance abuse among teenagers and only collect statistics from a research sample of public high school students, then the sample is biased because you excluded teenagers who are home-schooled or in private school, or teens who dropped out. Therefore, you were unable to make a well-rounded and accurate conclusion about your information. Sampling bias skews your data and makes your research incorrect.