Will I have a random or nonrandom sample and is my sample of sufficient size that I can assume the scores approach that of a normal distribution? What is my anticipated sample size and will I have a sample of sufficient size such that I can conduct the statistical procedures I have planned to run? How you answer these questions will, to a degree, influence the questions you ask on your survey and help establish the response categories for the questions. Most importantly they will influence the kinds of statistical procedures you are able to conduct for your study. Constructing Your Response Categories - Establishing Your Level of Measurement If you are constructing your data collection instrument, you have the opportunity to establish the level of measure for many of your variables. As an example, the variable education can be constructed in such a way that your data may be a nominal, ordinal, or an interval/ratio measure. Education as a nominal measure: Do you have a high school diploma? ____Yes ____No Education as an ordinal measure: What is your current standing? ___Senior ___Junior ___Sophomore ___Freshman Education as an interval/ratio measure: How many years of education do you have? ______Years As you examine the examples above of how you could construct a question about one’s level of education, you should recognize that designing and constructing a survey instrument is both a science and an art, and you should think of a question in terms of its response categories and level of measure. The next section further illustrates the importance of the response categories of your questions. Associating Response Categories of a Question to Statistical Procedures This section presents the relationship between level of measure of the response categories of a question and possible basic statistical procedures you can conduct. As noted earlier and illustrated in sections still to come, you should think in terms of both univariate and bivariate data analysis. The tables below provide a basic guide for the types of univariate and bivariate data analysis you can conduct, based on the measurement level of your variables. In the tables below, measurement level refers to the response categories for a given question on a survey.
Will I have a random or nonrandom sample and is my sample of sufficient size that I can assume the scores approach that of a normal distribution? What is my anticipated sample size and will I have a sample of sufficient size such that I can conduct the statistical procedures I have planned to run? How you answer these questions will, to a degree, influence the questions you ask on your survey and help establish the response categories for the questions. Most importantly they will influence the kinds of statistical procedures you are able to conduct for your study. Constructing Your Response Categories - Establishing Your Level of Measurement If you are constructing your data collection instrument, you have the opportunity to establish the level of measure for many of your variables. As an example, the variable education can be constructed in such a way that your data may be a nominal, ordinal, or an interval/ratio measure. Education as a nominal measure: Do you have a high school diploma? ____Yes ____No Education as an ordinal measure: What is your current standing? ___Senior ___Junior ___Sophomore ___Freshman Education as an interval/ratio measure: How many years of education do you have? ______Years As you examine the examples above of how you could construct a question about one’s level of education, you should recognize that designing and constructing a survey instrument is both a science and an art, and you should think of a question in terms of its response categories and level of measure. The next section further illustrates the importance of the response categories of your questions. Associating Response Categories of a Question to Statistical Procedures This section presents the relationship between level of measure of the response categories of a question and possible basic statistical procedures you can conduct. As noted earlier and illustrated in sections still to come, you should think in terms of both univariate and bivariate data analysis. The tables below provide a basic guide for the types of univariate and bivariate data analysis you can conduct, based on the measurement level of your variables. In the tables below, measurement level refers to the response categories for a given question on a survey.
Data%20Analysis%20Guide_0.docx