Quantitative data
Quantitative data refers to information that is expressed numerically or can be measured
Quantitative data refers to information that is expressed numerically or can be measured. It usually involves numerical values that represent quantities or amounts. This type of data is objective and can be analyzed using mathematical techniques and statistical methods.
Examples of quantitative data include:
1. Height of individuals
2. Temperature readings
3. Number of sales made
4. Scores on a test
5. Quantity of products produced
6. Weight of objects
Quantitative data can be further classified into two types: discrete and continuous data.
1. Discrete data: This type of quantitative data consists of separate, distinct values. These values are typically whole numbers and cannot have intermediate values. For example, the number of siblings a person has, or the number of students in a classroom, are discrete data as they cannot take on fractional or intermediate values.
2. Continuous data: Continuous data, on the other hand, can take on any value within a specific range. It can include fractional or decimal values. Examples of continuous data include height, weight, or temperature. Continuous data can be measured and divided into smaller units or intervals, such as inches, grams, or degrees Celsius.
Quantitative data is important in various fields, such as statistics, economics, science, and research, as it allows for numerical analysis, comparison, and inference. It helps in making informed decisions, identifying patterns, and drawing conclusions based on numerical evidence.
More Answers:
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