Data types and measurement scales are crucial for effective business analysis. Understanding the difference between qualitative and helps choose appropriate collection methods and analysis techniques.
Measurement scales - nominal, ordinal, interval, and ratio - determine how data can be analyzed and interpreted. Matching the right scale to business scenarios ensures accurate insights and informed decision-making.
Types of Data
Qualitative vs quantitative data
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represents attributes, characteristics, or categories that cannot be measured numerically
Collected through observations, interviews, or open-ended survey questions (colors, emotions, opinions)
Quantitative data represents numerical values or quantities that can be measured and expressed using numbers
Collected through , with closed-ended questions, or observations (height, weight, temperature, sales figures)
Types of measurement scales
categorizes data into mutually exclusive groups without any order or hierarchy
(male, female), marital status (single, married, divorced), eye color (blue, brown, green)
categorizes data into ordered groups, but the differences between categories are not necessarily equal