BNAD 276 Lecture 1: 1.1-Qualitative vs. Quantitative

• School: University of Arizona
• Department: Business Administration
• Course: BNAD 276
• Professor: brentmarinan

Document Summary

Richness of data increases as you move down (n>o>i>r) Data are simply categories for grouping the data. Qualitative values may be converted to quantitative values for analysis purposes. Can only be defined into like 0 or 1---nyse or nasdaq. Ordinal data may be categorized and ranked with respect to some characteristic or trait. Instructors are often evaluated on an ordinal scale---excellent, good, fair, poor. Difference between categories are meaningless because the actual numbers used may be arbitrary. There is no objective way to interpret the difference between instructor quality. Data may be categorized and ranked with respect to some characteristic or trait. Differences between intervals are equal and meaningful. Thus the arithmetic operations of addition and subtraction are meaningful. No absolute zero or starting point defined. Like the temperature on a fahrenheit thermometer. Ratio data may be categorized and ranked with respect to some characteristic or trait. Differences between interval values are equal and meaningful.