## Quantitative Analysis: Variables, Z Scores, Population, and Output

Respond to the following short answer questions, be sure to label each questions.

If you have categorical, ordered data (such as low income, middle income, high income) what type of measurement would you have? Why?

D2.3.2. (a) Compare and contrast nominal, dichotomous, ordinal, and normal variables. (b) In social science research, why isnt it important to distinguish between interval and ratio variables?

D2.3.3. What percent of the area under the standard normal curve is within one standard deviation of (above or below) the mean? What does this tell you about scores that are more than one standard deviation away from the mean?

D2.3.4. (a) How do z scores relate to the normal curve? (b) How would you interpret a z score of 3.0? (c) What percentage of scores is between a z of 2 and a z of +2? Why is this important?

D2.3.5. Why should you not use a frequency polygon if you have nominal data? What would be better to use to display nominal data?