Analysis of Survey Data
53 Summary
Chapter 9 has focused on the analysis of quantitative data associated with survey data. As previously noted, it is not the intention of this introductory chapter to delve too deeply into quantitative analysis. As such, this chapter has focused briefly on univariate data analysis. If you are interested in learning more about the analysis of quantitative survey data, we encourage you to take some courses in statistics. The quantitative data analysis skills you will gain in a statistics class could serve you quite well should you find yourself seeking employment one day.
Key Takeaways
- Non-response bias occurs when only those who have strong opinions about a study topic return the survey. Consequently, the findings so not represent how things really are or, at the very least, are limited in the claims that can be made about patterns found in the data
- Univariate analysis is the most basic form of analysis that quantitative researchers conduct. Ir includes frequency distributions and measures of central tendency.
- Measures of central tendency tell us what the most common, or average response is on a question and can be taken for any level variable: nominal, ordinal, interval and ratio. There are three kinds of measures of central tendency: modes, medians, and means.
- Mode refers to the most common response given to a question. Modes are most appropriate for nominal level variables. Median is the appropriate measure of central tendency for ordinal-level variables. Mean is the appropriate measure of central tendency for interval- and ratio-level variables. To obtain a mean, one must add the value of all responses on a given variable and then divide that number of the total number of responses.
- Bivariate analysis allows us to assess covariation among two variables. This means we can find out whether changes in one variable and then divide together with changes in another.
- Covariation means we can find out whether changes in one variable occur together with changes in another
- Contingency tables are used to demonstrate how variation on one variable may be contingent on variation on the other.
References
Babbie, E. (2010). The practice of social research (12th ed.). Belmont, CA: Wadsworth.
McKay, S. (2015, April 13). Are you using a questionnaire or survey to collect data? Retrieved from https://www.surveygizmo.com/resources/blog/taking-the-question-out-of-questionnaires/
Palys, T., & Atchison, C. (2014). Research decisions: Quantitative, qualitative, and mixed methods approaches (5th ed.). Toronto, ON: Nelson Education Ltd.
Schmitz, A. (2012). Principles of sociological inquiry; Qualitative and quantitative methods. Washington, DC: Saylor Academy.
