Final answer:
The measure scales being used are ordinal for high school soccer players' athletic ability, ratio for baking temperatures, and nominal for the colors of crayons. Quantitative data is often measured with ordinal, interval, or ratio scales, while qualitative data typically uses the nominal scale.
Step-by-step explanation:
The question you've asked pertains to the levels of measurement used in data analysis which can significantly influence the type of statistical methods that are applicable. The levels of measurement include nominal, ordinal, interval, and ratio scales, each representing different complexities and types of data. Here are the answers to the types of measure scales being used in the examples provided:
- High school soccer players classified by their athletic ability (superior, average, above average) use an ordinal scale since the categories have a meaningful order.
- Baking temperatures for various main dishes (350, 400, 325, 250, 300) use a ratio scale since there is a true zero point and the differences and ratios between temperatures are meaningful.
- The colors of crayons in a 24-crayon box use a nominal scale as they are categorical and do not have an intrinsic order.
Quantitative research data is countable or measurable, often using ordinal, interval, or ratio scales for thorough analysis. In contrast, qualitative research data often utilizes the nominal scale as it encompasses categories and labels without inherent ordering.