Statistics : Chapter 1.5 BIAS IN SAMPLING

Data-entry Error :

Although not technically a result of response bias, data-entry error will lead to results that are not representative of the population. Once data are collected, the results typically must be entered into a computer, which could result in input errors.

Type of Question :

An open question : allows the respondent to choose his or her response. eg: What is the most important problem facing America's youth today? A closed question : requires the respondent to choose from a list of predetermined responses. eg: What is the most important problem facing America's youth today? (a) Drugs (b) Violence (c) Single-parent homes (d) Promiscuity (e) Peer pressure

BIAS IN SAMPLING

If the results of the sample are not representative of the population, then the sample has bias.

Nonresponse Bias

Non response bias exists when individuals selected to be in the sample who do not respond to the survey have different opinions from those who do. Non response can occur because individuals selected for the sample do not wish to respond or the interviewer was unable to contact them. All surveys will suffer from non response. Non response bias can be controlled using callbacks. Another method to improve non response is using rewards, such as cash payments for completing a questionnaire, or incentives such as a cover letter that states that the responses to the questionnaire will determine future policy.

Sampling Error versus Nonsampling Error

Non response bias, response bias, and data-entry errors are types of non sampling error. However, whenever a sample is used to learn information about a population, there will inevitably also be sampling error. Non sampling errors result from under coverage, non response bias, response bias,or data-entry error. Such errors could also be present in a complete census of the population. Sampling error results from using a sample to estimate information about a population. This type of error occurs because a sample gives incomplete information about a population.

Response Bias

Response bias exists when the answers on a survey do not reflect the true feelings of the respondent. Response bias can occur in a number of ways. Interviewer Error : A trained interviewer is essential to obtain accurate information from a survey. A skilled interviewer can elicit responses from individuals and make the interviewee feel comfortable enough to give truthful responses. Misrepresented Answers : Some survey questions result in responses that misrepresent facts or are flat-out lies. Wording of Questions : The way a question is worded can lead to response bias in a survey, so questions must always be asked in balanced form. Ordering of Questions or Words : Many surveys will rearrange the order of the questions within a questionnaire so that responses are not affected by prior questions.

Sampling Bias

Sampling bias means that the technique used to obtain the sample's individuals tends to favour one part of the population over another. Any convenience sample has sampling bias because the individuals are not chosen through a random sample. Sampling bias also results due to under coverage, which occurs when the proportion of one segment of the population is lower in a sample than it is in the population. Under coverage can result if the frame used to obtain the sample is incomplete or not representative of the population. Some frames, such as the list of all registered voters, may seem easy to obtain; but even this frame may be incomplete since people who recently registered to vote may not be on the published list of registered voters. Sampling bias can lead to incorrect predictions.

Sources of bias in sampling

There are three sources of bias in sampling: 1. Sampling bias 2. Nonresponse bias 3. Response bias