Question

researchers are interested in the satisfaction level of residents surrounding available healthcare. they use online surveys to conduct their research. help them answer the following questions:
will the researchers use primary or secondary data?
:
in sampling people from the province, what region is the best sampling in order to be the most representative of ontario? why?

does this study involve qualitative or quantitative data? why?

based on your knowledge of collecting data, come up with 4 different topics of interest to you involving a relationship between 2 variables.
1.
2.
3.
4.

Explanation:

1. Will the researchers use primary or secondary data?

Primary data is collected directly from the source (e.g., surveys, interviews). Here, researchers conduct online surveys on residents, so they collect data firsthand. Secondary data is pre - existing (e.g., census data, reports). Since they are creating surveys to gather new data, it's primary.

To be representative, a sample should reflect the diversity of the population. Ontario has different regions (urban, rural, different cities, etc.). Using a stratified random sampling across different regions (e.g., Toronto, Ottawa, rural areas) or a simple random sample from the entire province's population frame (list of all residents) would help. A representative sample should include people from different geographical, demographic, and socioeconomic regions. For example, if we only sample from Toronto, it won't represent rural Ontario. So, a sampling method that includes multiple regions (stratified or cluster sampling with regions as strata/clusters) is best. The best region to sample from is not one specific region, but a cross - section of all regions in Ontario. Because Ontario has diverse populations in different regions (e.g., urban centers like Toronto, smaller cities like Hamilton, rural areas), sampling from multiple regions (using methods like stratified sampling by region) ensures that all segments of the Ontario population are represented.

Quantitative data is numerical (e.g., ratings, counts), qualitative is non - numerical (e.g., opinions in words, descriptions). If the online survey has questions with numerical responses (e.g., rating satisfaction on a 1 - 5 scale) or counts (e.g., number of healthcare visits), it's quantitative. If it's open - ended questions with text responses (e.g., "Describe your healthcare experience"), it's qualitative. But typically, satisfaction surveys often use numerical scales (quantitative) or can have both. Assuming the survey asks for numerical ratings (e.g., 1 - 10 for satisfaction), it's quantitative. If it's about collecting numerical data (e.g., satisfaction scores, number of healthcare providers used), it's quantitative. If it's about descriptive, non - numerical data (e.g., types of healthcare issues), it's qualitative. Given the context of "satisfaction" (often measured numerically), it's likely quantitative. Because if the survey collects numerical data (e.g., satisfaction ratings on a scale, number of healthcare services used), it's quantitative. If it were collecting non - numerical descriptions (e.g., written accounts of experiences), it would be qualitative. Based on the common use of surveys for satisfaction (often numerical scales), it's quantitative.

Answer:

Primary data. Because the researchers are conducting online surveys to collect data directly from the residents (the source), rather than using pre - existing data.

2. In sampling people from the province, what region is the best sampling in order to be the most representative of Ontario? Why?