How to Recognize Potential Biases in Data Collection

Data collected through surveys, questionnaires, interviews and experiments is effected by a variety of factors. The term "bias" is often used to describe internal and external factors that inadvertently contaminate the data collected and skew the results. Encountering biases is expected in most situations. The problem arises when researchers fail to recognize the bias.

Instructions

1. Develop interview questions and surveys carefully. The questions need to be clear and concise without any tendency to lead or judge the person answering the survey. Realize that false information, whether intentional or not, is possible if questions are not clear.

2. Keep the subject focused when conducting an in-person interview. Make sure the interviewee is not avoiding the question and is comfortable. This creates a safer environment and increases the chances that you get a truthful answer rather than one aimed to please the interviewer. Interviewees are often more likely to respond in a way that they feel is more favorable in the eyes of the interviewer, even if this requires them to lie.

3. Remember that the social environment and the presentation of the researcher influences the answers given by an interviewee. Be aware of the attitude, social class, gender, the dress, personality, comfort level and general assumptions of the interviewee of the researcher. All play a part in the information the interviewee feels comfortable given.

4. Observe and note non-verbal cues and behaviors of the interviewee, but realize that these are sometimes interpreted incorrectly. Also realize the interviewer sends out non-verbal cues to the interviewee. Keep non-verbal behavior open, welcoming, encouraging but by no means judgmental or condescending.