Answer questions in two ways:
1. What are the differences between quantitative and qualitative?
Quantitative is data that is collected through observation and findings are presented through words and dialogue instead of numbers.
Qualitative is data that is collected by numerical information such as tests, counts, and measurements. The results are given in the form of numbers.
For the Scenario the qualitative data are things like interests, attitudes, and skills of the residents. The example of qualitative data in the scenario was the sign up sheet that gave the number of people engaged in activities.
2. What are the levels of data you might encounter?
Nominal Data is the type of data that is based on one principle such as type, gender, or age.
Ordinal Data is also the type of data based on one principle. This type of data conveys some sort of rank or order. The book describes a scale as being a good example for ordinal data.
Interval Data have rank like ordinal data, but they also have intervals. Most numerical scales have intervals. This type of data contains no absolute zero and therefore the so there can be no assumption between negative and positive numbers.
Ratio Data is data a combination of nominal data, ordinal data, and interval data, with the addition that in ratio data there is an absolute zero. Examples are weight and height.
In the scenario nominal data, such as age and gender of the residence, can be used as well as the name of the activities that they are involved in. Ordinal data could be found on the sign up sheet to see which activities ranked higher in opinion of the residence. Interval data could be used when ranking the level of health benefits in a certain program. Ratio Data could be used when determining overall health such as percentage of weight lost or affects on blood pressure.
3. What are some instruments you might use or develop?
Interview: Gather information by asking question to gain information for qualitative data. In the scenario the residents could be interviewed to see how they feel about the program and how it affects them.
Scales: can be used to gather nominal data, which can be done by having the staff and residents rate their experience with a program.
Sentence Completion: This is done by giving the participant a complete a sentence, thought or problem. For the scenario it would be a good tool to ask participants how, in their opinion, would the improve conditions.
Tests: To gain quantitative data through administering tests that is given and measured the same way every time. The participants could take a test to have a measurement of skills acquired through different activities.
Observational Data: In the book it is described as a method used by evaluators to assess program delivery. It can be unobtrusive, where the person being observed does not know that they are being observed, and obtrusive where the do know. In the scenario the participants activity and involvement can be observed either obtrusively or unobtrusively.
This Data Analysis tutorial is presented by The University of the West of England, and contains a great deal of detail of the process of data analysis. It also gives in depth examples and information of qualitative and quantitative analysis. For instance when it discusses issues of qualitative analysis such as trustworthiness, credibility, transferability, dependability and conformability. It also goes in depth with issues concerning quantitative analysis such as validity and reliability.