Want this question answered?
Occupation is nominal data. There is not an order to the category occupation, so that eliminates ordinal and interval.
Age is none of the items listed. Age is ratio data.
Metric data is any reading which is at least at an interval scale, as opposed to non metric data, which can be nominal or ordinal. Weight, height, distance, revenue, cost etc. are interval scales or above. Hence they are metric data. On the other hand, satisfaction ratings, Yes/No responses, Male/Female readings etc., are non metric data.
Bar charts are used to summarise nominal or ordinal data.
Ordinal. Tests responses are usually correct or incorrect. This would be assigned a value and the number of correct answers is the score of the test. There is a logical order, a correct answer is better than an incorrect answer, so it is not nominal data. Even though we calculate averages, test responses are not interval data, as there is no meaning to the interval. See related link.
It is Ordinal:Order the data from smallest to largest or "worst" to "best".Each data value can be compared with another data value.
illustrate how you can express the age of group of persons as {1}nominal,{2}ordinal data,{3} interval data,{4}ratio data
Scales
The mode can be very useful for dealing with categorical data. For example, if a sandwich shop sells 10 different types of sandwiches, the mode would represent the most popular sandwich. The mode also can be used with ordinal, interval, and ratio data. However, in interval and ratio scales, the data may be spread thinly with no data points having the same value. In such cases, the mode may not exist or may not be very meaningful. www.quickmba.com/stats/centralten/
It is ordinal.
Ordinal statistics or data is classified as ordinal if the values can be rated on a scale or put i order. Ordinal data can be counted but never measured.
No, but the answers provide ordinal data.