Week 12 MSN 5300: Correlational research

Week 12 MSN 5300: Correlational research


Please replies with 200 words in each one answer.

1.Correlational analysis is a useful statistical method for determining the links between two or more variables. This method’s main goal is to determine if differences in one variable are related to changes in another. Correlational research, in contrast to experimental methods, concentrates on monitoring and quantifying naturally existing associations rather than manipulating variables. Correlational analysis has several goals, including investigation, predicting, and developing hypotheses.

Investigating correlations between variables is one of correlational analysis’s main goals. Researchers can learn more about the nature of the connection between two variables by measuring the degree and direction of association between them. When nothing is known about the variables being studied, this examination is especially helpful in the early phases of scientific discovery. For further explorations, correlational studies provide the framework by assisting researchers in identifying possible variations and patterns.

Prediction is another essential goal of correlational analysis. Researchers can utilize this knowledge to predict one variable depending on the value of another if correlations between variables have been discovered. The correlation between the number of hours of sleep and academic achievement is an example of connected variables. Several research favor the association between sleep and academic achievement since students who regularly obtain more sleep tend to receive higher scores (Maheshwari & Shaukat, 2019)

In addition, correlational analysis is essential for formulating research hypotheses. New questions and ideas that direct further research can be generated by the correlations between variables that have been found. Although correlation does not indicate causation, it may be a beneficial tool for formulating and evaluating theories on possible causal connections.

In summary, there are many different uses for correlational analysis, including theory validation, hypothesis development, exploration, and prediction. Correlational investigations considerably increase scientific understanding in a variety of fields by exposing correlations between variables, making a valuable tool to help make decisions.

2. Correlational analysis in research, especially in the nursing field, constitute an important resource to study the association that might exist among different variables of interest without manipulating or controlling any of them, but mostly observing. It is characterized by being a method that does not consume a lot of time or finances and serve as a tool to analyze, create hypotheses and evidence based guidelines.

This method of investigation is usually applied in 2 scenarios: when researcher want to evaluate non-causal relation between two elements or when the objective is to study a causal link among the variables (Eckel, 2023). In other words, the principal purpose of correlational analysis is to observe and predict.

Once the research obtain the results, it can have three possible outcomes which are classified depending on a numerical value known as correlational coefficient which can vary from -1.00 (negative) to +1.00 (positive). These results are then classified as positive (when the variables under study increase or decrease at the same time), negative (referred as a result in which the variable gives opposite results, that is one increase while the other decrease) or non-correlational (when there result is 0, indicating no relationship among the variables) (Cherry, 2023).

In relation to the methods applied to collect data for correlational analysis we can use surveys, naturalistic observations or secondary data. Depending on the objective and variable to study, researchers need to choose the right methods of data collection. For example, in the case of investigating a population point of view questionnaire can be used; if the goal is to observe behavioral patterns in its normal setting, then the naturalistic observation is used. Finally, if the research plan to compare data that already exists, using information obtained by other researchers in similar studies the method that is used would be the secondary or archival data.

The importance of correlational analysis in nursing is given by the fact that it helps to understand the relationship between variables, serving as a guide for new line of investigations, it can provide predictive insights, evaluate interventions and provide quality improvement in terms of effort by helping to identify which areas of nursing practice needs changes and which are correctly done in order to provide better quality of care.

However, before deciding to apply this method of investigation, researcher should take in consideration the limitations of establishing causal effect among variables, because in this case the study will demand deeper experimental designs (Jansen, et al., 2021).