Debate the advantages and disadvantages of quantitative and qualitative research based on your research experiences.Please include the name of the person or question to which you are replying in the subject line. For example, Toms response to Susans comment.Friendly reminder to begin your Discussion Initial Post as early in the week as possible. Waiting till the end of the Unitsacrifices your learning, sharing and communication with one another.Kindly address the discussion question(s) submitting a reflective response.Reflective defined is characterized by or manifesting careful thought : a thoughtful essay. occupied with or given to thought ; contemplative; meditative; reflective: in a thoughtful mood, careful, heedful, or mindful.ALSO PLEASE REPLY TO ANOTHER STUDENTS COMMENT BELOWERIC:Looking at each one of the quantitate and qualitative research method, it’s important to understand how each method is used.As we dive into the quantitative method, this method will use the approach of collecting the faces by using statistical, computation, and mathematical data. These are all what I call hard facts which can be supported and measured in several ways to verify the accuracy of the data.Now as we understand the qualitative method, the collection of data is not like quantitative, face finding, but more based on opinions, concepts and characteristics of the information that which to be gathered.There are several advantages and disadvantages to both methods. First, advantages to quantitative research can allow the data to be checked and confirmed as valid, and in turn give you clear direction based on the study, these statistical tests will be straight forward and will not allow miss guidance. One other positive with quantitative research comes with the mathematics side, many do not understand the math that it requires in the background and will give a level of credibility of the data.Likewise, the downfall of quantitative, is the data could be limited, in times one may want to have the data be concrete solid, bit the data is not there to formulate the numbers. The hypothesis needs to be carefully though out and constructed in an orderly fashion. This will carry over to the model as if there are any flaws with the model, the outcome will be non-void, and allow for the data to be debated.