By Fred Johnson Norman L. & Leone
Read or Download Statistics and Experimental Design In Engineering and the Physical Sciences Volume I PDF
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Extra resources for Statistics and Experimental Design In Engineering and the Physical Sciences Volume I
Example text
Moving on to data analysis Because you will get only one chance at collecting any primary data you need, it is vital that your data collecting tool is the best that you can construct to answer your research questions. When it comes to coding, we suggest you go for the belt-and-braces method, and use the following two-stage method when designing the questionnaire or interview schedule: 1. Create a master document, in which you note down for each question or statement the bit of literature or theory that it is connected with or refers to.
While you are collecting the responses during semi-structured interviews, you, as the interviewer, have the opportunity to rephrase the question or to reassure the interviewee, and thus to coax a response, but with a questionnaire, there is nothing you can do to encourage a respondent not to go down the ‘don’t know’ route. There are, however, two ways to deal with ‘don’t know’ responses when it comes to analysing them. If you are using a questionnaire and have given a question or statement a ‘don’t know’ alternative, along with the ‘yes’ and ‘no’ alternatives, you should analyse the three categories.
With numerical data, the variables that you are concerned with include measurements and counts such as weight, height, age, or income, and so on, and these are obviously expressed as numbers. Because these data have numerical meaning, you can describe them in more ways than you can describe categorical data. What is comforting is that these descriptive statistics can often be done without needing complicated statistical software – your fingers and some mental arithmetic, or a calculator, will do just as well.
