The Levels of Measurement of Data Research

The questions in this instrument are weighted a numerical value of zero to three, with three being the highest score on each question.

Questionnaire is set of questions which could be written or multiple choice question given to the individuals or groups to find the factual information.

The answers are measured on a 5 point Likert scale from questions 1-7 and Yes or No format for questions 8 -10. Responses are recorded and interpreted according to the scoring key and norms. The results are then displayed in the form of a pie chart comparing each sector.

2. Data from Likert scales and continuous (e.g. 1-10) rating scales are quantitative. Allows you to measure their feeling on a scale of 1

Measurement that shows the order or rank of items. An example of ordinal could be ranking places in a contest, or test scores.

1. The researchers analyzed the data they collected as though it were at what level of measurement?- The correct answer is Interval/ratio.

b. Ordinal: This is a measurement that represent the order of a particular stat. A good example of this would the placement in a contest, 1st, 2nd, and 3rd.

Answer: This is a ordinal variable since education level is ordered from less to higher education and is put into 4 categories.

Ordinal data has the variables that include rank and satisfaction. An everyday example of ordinal data can be surveys.

The first question I analyzed, “How prepared on a scale of 1-5, (five being 100% prepared) are you for an earthquake?” used a Likert-type scale to gain insight into how prepared participants perceived themselves to be for an earthquake. In my data analysis I assigned qualitative descriptions to the quantitative ratings people gave as their preparedness level as

The first control variable, people the respondent knows suicide over lifetime, was measured as a nominal variable in the data set, but has a quantitative type of categories, ranging from 0 to 10, as well as 20, 21,50, 70, 95: 1 or more, number unknown, with missing values: 98 Don’t know, 99. No answer. I recoded this variable into a nominal variable with three categories: 0. None, 1. Few and 2. More.

Ordinal scales use labeling characteristics similar to nominal scales but in this case, it uses the numbers for the ability to order the data. This scale is a higher level of measurement and is used mostly to show the rank order of the items to be reviewed. The operations determine which is greater or lesser than another in the same list. For example, if there were a questionnaire about a person’s preference of restaurants, the questionnaire would give the respondent a few choices to review. If the example has five choices, the respondent would choose one to five with the number five as most desired. Then the individual will rank the most desired restaurant by placing the number five next to the name of the restaurant he or she prefers the most. This helps the questionnaire determine which restaurant is preferred greater than others. Then the measure of central tendency is the median, and the percentile would be used for measuring dispersion (McDaniel, 2006).

The levels of measurements that variables can take are: (1) scale or continuous; (2) ordinal; (3) nominal; (4) interval; (5) Dichotomous; (6) Ratio.

Nominal – The lowest, simplest, level of measurement. This scale of measurement has researchers attach labels to attributes that are not rank ordered in any way. That is, “colors” would be a good example of a nominal scale of measurement. “Green” “Blue” “Orange” would be

▪ This structure creates bias with the wording. A numerical scale from 1-5 or 1-7 would be ideal.