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Experimental research is an analysis carried out to get to conclusions utilizing sets of different variables. This type of research is the most common one used in many different fields. It consists of carrying an experiment or investigation to prove or refute a certain hypothesis. Thus, it utilizes controlling a constant (independent variable) which is the first set, with which you reference to in order to contrast the following set the dependent variable. Scenarios under which one can carry out an experimental analysis are when one wants to appreciate the reason and effect, when duration is necessary to have link between reason and effect and when the is unalterable instance between reason and effect. There are three subgroups of this type of research, namely true experimental research, quasi-experimental research and pre-experimental research. Pre-experimental analysis involves a collection or a set of collections to be analyzed following circumstances of reason and effect, an example for experimental analysis is quantitative analysis. Quantitative analysis uses three important dominant variables namely extraneous, independent and dependent. An example of a quasi-experiment was used when a study was done to investigate how student nurses can be taught to practice safe drug administration by use of medication simulations enhanced by integrated information technologies in an undergraduate-nursing curriculum where 83 third-year BSN students were randomized into intervention or control groups. Control groups participated in standard training while the intervention group received additional clinical simulation experience and debriefing sessions focused on medication safety practices. Participant knowledge was measured using pre/post Medication safety knowledge assessment and competency was evaluated using the Medication Safety critical eleCraig,2020). The intervention group results indicated that they had gained more knowledge than the control group. Experimental research enables the researcher to experiment in controlled surroundings, hence it is highly managed enabling the researcher to have a sustainable influence over variables to manipulate the outcome. Thus, it can be used to trail and challenge new findings and conceptions. There is also less probability of bias in this kind of analysis.
Non-experimental analysis involves no controlling or manipulating of variables in order to obtain the specific desired outcomes. In this kind of analysis variables are just analyzed and recorded as they naturally exist without any form of alteration. For this type of analysis to be applied, there must be no direct analysis subject concerning any form of link between the two sets of diverse variables. It can also be applied when the researcher cannot find enough analysis data about the analysis subject and when the analysis fails to designate conditions to the subjects. This analysis type can be divided into three subgroups, which are observational analysis, correlation analysis and cross-sectional analysis. Cross-sectional analysis consists of comparing between a set of already available collection of people. Correlational analysis involves contrasting two variables based on their statistical link, this is done without altering or controlling the independent variable. An example of a non- experimental study is a correlational research study which was conducted with a convenience sample of 92 participants. The primary aim of this study was to explore the predictors of medication adherence among inpatients with schizophrenia hospitalized at tertiary hospitals in Singapore. Post-hoc analysis revealed that insight, religion, side effects, types of antipsychotics, social support from significant others, nurse-client relationship, were significant predictive factors. (Tham, 2018). Results from this study added knowledge to the nursing literature about medication adherence of schizophrenia patients
Respond to the above write up.  Support your response with peer reviewed articles.