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Measurement scales
This document discusses different types of measurement scales used in research: nominal, ordinal, interval, and ratio. Nominal scales involve categories with no intrinsic ordering, while ordinal scales involve ordered but non-quantified categories. Interval scales have equal intervals between points, and ratio scales have a true zero point, allowing ratios to be calculated. The type of scale used constrains the types of analysis that can be performed on the data. Questions can be designed to collect different types of data depending on the scale, from multiple choice to rankings to numerical values.
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Measurement scales
- 1. Types of Data& Measurement Scales: Nominal, Ordinal, Interval and Ratio Research Writing
- 2. 4 Measurement Scales(or types of data) • nominal, ordinal, interval and ratio • They are simply ways to categorize different types of variables
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- 4. Survey Question Types • • • • • Open-endedtext questions Multiple choice questions Ordinal scale questions Interval scale questions Ratio scale questions The type of data generated by the survey question constrains the type of analysis you can perform.
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- 6. • These scalesare mutually exclusive (no overlap) and none of them have any numerical significance) http://www.mymarketresearchmethods.com/types-of-data-nominal-ordinal-interval-ratio/
- 7. Nominal Data Example •Dichotomous: a nominal scale with only two variables
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- 9. 2) Ordinal Data:Rank Order Scale create an ordinal scale of preference • Rank order scaling questions allow a certain set of variables to be ranked based upon a specific attribute or characteristic. http://www.questionpro.com/a/showArticle.do?articleID=survey-questions
- 10. Ranking questions arebest to use when all the choices listed should be ranked Ranking questions are best to use when all the choices listed should be ranked according to a level of specification (e.g. level of importance). according to a level of specification (e.g. level of importance). If you have a question in which you need the respondents to indicate what items If you have a question in which you need the respondents to indicate what items are the “most important” to “least important,” then you can set up a ranking are the “most important” to “least important,” then you can set up a ranking question (Waddington 2000). question (Waddington 2000). http://s3.amazonaws.com/SurveyMonkeyFiles/SmartSurvey.pdf
- 11. Rating (Lickert* )Scale: ordinal? (non-numeric concepts like satisfaction, happiness, etc.) ( • the order of the In each case, we know that a #4 is better than In each case, we know that a #4 is better than a #3 or #2, but we don’t know–and cannot a #3 or #2, but we don’t know–and cannot quantify–how much better ititis. quantify–how much better is. * pronounced 'lick-urt' with a short "i" sound values is what’s important and significant, but the differences between each one is not really known http://www.mymarketresearchmethods.com/types-of-data-nominal-ordinal-interval-ratio/
- 12. surveying the frequencyof something like behavior or attitude. It is best to present the rating scale in a logical or consistent order. Therefore, it makes sense to order the ranking or rating choices from low to high (e.g. Strongly Disagree to Strongly Agree going from left to right). http://s3.amazonaws.com/SurveyMonkeyFiles/SmartSurvey.pdf • Rating type questions are used when
- 13. Interval Scale • Itis an interval scale because it is assumed to have equidistant (equal distance) points between each of the scale elements. This means that we can interpret differences in the distance along the scale. We contrast this to an ordinal scale where we can only talk about differences in order, not differences in the degree of order .
- 14. Interval Scale • Whenyou are asked to rate your satisfaction with a piece of software on a 7 point scale, from Dissatisfied to Satisfied, you are using an interval scale • it is important that the space between each option, whether it's a number range or a feeling range, are equal. • scales asking about agreement strength, likelihood or satisfaction (i.e. very unsatisfied, unsatisfied, neither satisfied nor unsatisfied, satisfied, very satisfied).
- 15. • …Similar toordinal, but the intervals between • • the values of the response options are evenly spaced …Can be used for any quantitative variable …Measures variables that fall into logical ranges • Example: What was your undergraduate GPA upon graduation? a) 3.5-4.0 b) 3.0-3.49 c) 2.5-2.99 d) 2.0-2.49 http://www.virginia.edu/processsimplification/resources/survey_design.pdf
- 16. According to JamesDean Brown (University of Hawai‘i at Manoa) • Interval scales show the order of things, but with • • equal intervals between the points on the scale. Thus, the distance between scores of 50, 51, 52, 53 and so forth are all assumed to be the same all along the scale. Test scores are usually treated as interval scales in language research. Scales based on Likert items are also commonly treated as interval scales in our (education/social research) field. http://jalt.org/test/PDF/Brown34.pdf
- 17. Ordinal & IntervalExample http://cdn.informationmanagement.com/media/assets/article/1023904/few_fig3.gif
- 18. Ratio Scale • Ratioscales differ from interval scales in that they have a zero value and points along the scale make sense as ratios. For example, a scale like age can be zero, and it makes sense to think of four years as twice as old as two years http://survey.cvent.com/blog/cvent-survey-blog/guide-to-the-five-types-of-survey-questions
- 19. • When respondentsare asked to tell us some physical measure, such as income, years of education, or how long their phone call was on hold, these are ratio scale questions. The data they provide have a true zero. (On an interval scale, a zero response option is simply arbitrary. Zero income, for example, is real.) • Frequently, we solicit ratio data with what appears to be an ordinal • scale with response options presented in ranges, such as if we were to ask for the number of years of education the person had achieved, asking the respondent to check one of the following options: 1) 1 to 12 years, 2) high school degree, 3) associates degree, 4) bachelors degree, 5) graduate degree. While the question looks ordinal, we could treat the data as ratio in our analysis. Why present ranges? – First, it's faster for the respondent to answer the question, lowering respondent burden. – Second, it's less invasive to ask someone to check an income range, for example, then to ask them their annual income. Would you tell a stranger your income level? Probably not, but you might be willing to check a box that says your income is $50,000 to $75,000 per year. http://www.greatbrook.com/survey_question.htm
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- 21. • Nominal: modecrosstabulation - with chi-square, etc. • Ordinal: use non-parametric statistics, i.e. Median and mode, rank order • http://efox.cox.smu.edu/mktg3342/dataanalysis.pdf http://www.csse.monash.edu.au/~smarkham/resources/scaling.htm Measurement correlation, non-parametric analysis of variance – Modelling techniques can also be used with ordinal data. Interval: Interval scale data would use parametric statistical techniques: – Mean and standard deviation Correlation - r Regression Analysis of variance Factor analysis – Cronbach analysis – Plus a whole range of advanced multivariate and modelling techniques • Ratio: variables which are ratio scaled include weights, lengths and times. virtually all statistical operations can be performed on ratio scales
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