The first rule is to design the questionnaire to fit the medium. Phone interviews cannot show pictures. People responding to mail or Web surveys cannot easily ask “What exactly do you mean by that?” if they do not understand a question. Intimate, personal questions are sometimes best handled by mail or computer, where anonymity is most assured.
While the Survey System will let you easily combine surveys gathered using different mediums; it is not usually recommended that you do so. A mail survey will often not give the same answers as the same survey done by phone or in person. If you used one method in the past and need to compare results, stick to that method, unless there is a compelling reason to change.
Kiss – Keep it Short and Simple:
If you present a 20-page questionnaire most potential respondents will give up in horror before even starting. Ask yourself what you will do with the information from each question. If you cannot give yourself a satisfactory answer, leave it out.
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Avoid the temptation to add a few more questions just because you are doing a questionnaire anyway. If necessary, place your questions into three groups: must know, useful to know and nice to know. Discard the last group, unless the previous two groups are very short.
Start with an introduction or welcome message. In the case of mail or Web questionnaires, this message can be in a cover page or on the questionnaire form itself. If you are sending emails that ask people to take a Web page survey, put your main introduction or welcome message in the email. When practical, state who you are and why you want the information in the survey. A good introduction or welcome message will encourage people to complete your questionnaire.
Allow a “Don’t Know” or “Not Applicable” response to all questions, except to those in which you are certain that all respondents will have a clear answer. In most cases, these are wasted answers as far as the researcher is concerned, but are necessary alternatives to avoid frustrated respondents.
Sometimes “Don’t Know” or “Not Applicable” will really represent some respondents’ most honest answers to some of your questions. Respondents who feel they are being coerced into giving an answer they do not want to give often do not complete the questionnaire. For example, many people will abandon a questionnaire that asks them to specify their income, without offering a “decline to state” choice.
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For the same reason, include “Other” or “None” whenever either of these is a logically possible answer. When the answer choices are a list of possible opinions, preferences, or behaviors, you should usually allow these answers.
On paper, computer direct and internet surveys these four choices should appear as appropriate. You may want to combine two or more of them into one choice, if you have no interest in distinguishing between them. You will rarely want to include “Don’t Know,” “Not Applicable,” “Other” or “None” in a list of choices being read over the telephone or in person, but you should allow the interviewer the ability to accept them when given by respondents.
Sampling is Based on Two Premises:
One is that there is enough similarity among the elements in a population that a few of these elements will adequately represent the characteristic of the total population.
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The second premises are that while some elements in a sample underestimate the population value, others overestimate the value. The results of these tendencies are that a sample mean is generally a good estimate of population mean. A good sample has both accuracy & precision. An accurate sample is one which there is little or no bias or systematic variance.
A sample with adequate precision is one that has a sampling error that is within acceptable limits. A variety of sampling technique is available, of which probability sampling is based on random selection a controlled procedure that ensures that each population element is given a known nonzero chance of selection. In contrast non-probability selection is not random. When each sample element is drawn individually from the population at large, it is unrestricted sampling.
Summary:
1. The sampling distribution is a theoretical distribution of a sample statistic.
2. There is a different sampling distribution for each sample statistic.
3. The sampling distribution of the mean is a special case of the sampling distribution.
4. The Central Limit Theorem relates the parameters of the sampling distribution of the mean to the population model and is very important in statistical thinking.