Reply to these two discussion posts. They both have different question they have answered. Reply if you agree with there decription for the question and/or your thoughts.
Reply should be 100+ words for each. DO NOT COPY PASTE> DO NOT PLAGARIZE.
#1: What questions could a hypothetical random survey have to help benefit individuals in a working environment?
On Tuesday during class everyone was told to fill out a survey truthfully without given much else to go on other then that. Everyone’s answers were compiled into comprehensive data to help to see if correlation was present between different answers. An example of another survey is if you asked a workforce in the same corporation both before lunch and after lunch how drastically would the results of the survey differ. If they differed greatly the person was most likely just hungry and nothing really had to change at the workplace.
I was curious to see if any sets of questions would have correlations and if those correlations would be able to somehow tell someone what needs to be changed in a work environment.
#2: When conducting a study, what is the best balance between asking quantitative questions and qualitative questions?
From what we have talked about in class about psychology research and studies, I have been seeing a lot of similarities between conducting research in psychology and using machine learning. At least when the questions are quantitative, which I would imagine most studies are. However, in that light, one of the disadvantages to machine learning is that though algorithms can be great at finding specific relationships between variables, it is still up to us as humans to determine why these variables interact with each other the way they do.
I think that qualitative data can be much more helpful for solving the “why” as data is not always limited to something quantifiable. In the context of a psychology study, you could possibly receive feedback from a subject that may give insight to a person’s internal thinking process. This can definitely be useful for coming to scientific conclusions, but of course would be impractical if you have a dataset of hundreds or thousands of points.
The question remains then, in order to conduct the most beneficial and insightful study, how much quantitative data should be recorded in comparison to qualitative data? Which types of study would favor one or the other?