Final answer:
Nicole used secondary data analysis, which is part of quantitative sociology, to determine obesity rates in Texan cities, analyzing existing height, weight, and BMI data.
Step-by-step explanation:
Nicole is using c) Secondary data analysis to reach a conclusion on which cities in Texas have the highest rates of obesity. This method involves examining data that has already been collected for another purpose. She analyzes recorded height, weight, and BMI data to assess obesity rates. Secondary data analysis is a common method used in the field of quantitative sociology, where researchers look for patterns in data, often using statistical techniques. Moreover, Secondary data analysis is efficient and cost-effective since it makes use of existing data, circumventing the need for new, often extensive, data collection efforts.
In the context provided, quantitative data such as the number of fast-food restaurants in a neighborhood, residents' weights, or their BMIs would typically be used. These are numerical and can be analyzed statistically to test hypotheses such as the correlation between proximity to fast-food outlets and obesity rates. Conversely, qualitative data might involve deeper insights from things like in-depth interviews or content sources, which help to understand human behavior on a more nuanced level.
When considering the different types of data involved in survey-related research, the number of times per week an activity is performed is quantitative discrete data, duration is quantitative continuous data, and the colors of the houses are qualitative data. Nicole's study likely utilized quantitative continuous data, as BMI is a numerical value that is not restricted to integer values.