Which data type is numerical and suitable for statistical analysis?

Which data type is numerical and suitable for statistical analysis?

• A. Quantitative data
• B. Qualitative data
• C. Narrative data
• D. Descriptive data

Answer: (A)

Numerical data are measurements or counts that you can put into numbers and perform calculations with. This makes them ideal for statistical analysis, because you can compute averages, variability, distributions, and run tests or models. Qualitative data, on the other hand, are categories or labels (like product type or color) and aren’t numerical by default, so they don’t support arithmetic directly without first converting them into numbers. Narrative data are words and narratives; they require qualitative analysis or coding before numbers can be used in statistics. Descriptive data describes characteristics but isn’t itself a numeric data type used for statistical calculations. So the data type that is numerical and suitable for statistical analysis is quantitative data.

Numerical data are measurements or counts that you can put into numbers and perform calculations with. This makes them ideal for statistical analysis, because you can compute averages, variability, distributions, and run tests or models. Qualitative data, on the other hand, are categories or labels (like product type or color) and aren’t numerical by default, so they don’t support arithmetic directly without first converting them into numbers. Narrative data are words and narratives; they require qualitative analysis or coding before numbers can be used in statistics. Descriptive data describes characteristics but isn’t itself a numeric data type used for statistical calculations. So the data type that is numerical and suitable for statistical analysis is quantitative data.