Why do the Social Sciences depend so much on the “Analysis of Data?” What role does research play in the prediction, explanation, understanding, or analysis of human behavior and can that exploration sometimes be wrong? Explain.
RESPOND TO THE FOLLOWING 2 POSTS WITH AT LEAST 150-200 WORDS
Social Science, like any other scientific inquiry, depends on data analysis to accurately answer the questions that case studies are designed to answer. The research plays a crucial role in a study.
Research should be designed in such a way that the results don’t only match the prediction, but the results should accurately help answer scientific questions.
Research methods should be used to explain not only the results of a study, but explaining the methods used can also lend validity to the results.
Good research may help understanding in that the researcher can study past experiments in an effort to design better case studies that can uncover more accurate data.
As well, bad research, such as a biased study, will result in inaccurate data and faulty results can result from the analysis. As such, the exploration can sometimes be wrong.
The reason why social scientists depend so much on the analysis of data is, they seek to answer questions using rigorous methods and careful observations. These observations collected from the likes of field notes surveys, and experiments form the backbone of a statistical investigation. (Diez, Cetinkaya-Rundel, & Barr, 2017) Essentially social scientists seek to be unbiased and correct when answering a sociological question to solve societal problems. Lumen research dot com, cites this, “For many sociologist, the goal is to conduct research which may be applied directly to social policy and welfare, while others focus primarily on refining the theoretical understanding of social processes, subject matter ranges from the micro to the macro level.” (Lumen, 2018)
The role research plays in the prediction, explanation, understanding, or analysis of human behavior is to collect data to chart for evidence of human behaviors compared to variables which cause specified outcomes. As far as prediction goes if the outcome is positive, one may use this data to inform a client of what may help with a condition, on the contrary if the behavior is depression the data will be used to list triggers which cause such human behavior. Data gathered can be used to explain and understand human behavior in a learning environment; meanwhile analysis of human behavior could be used to scrutinize a subject for feedback.
The exploration and documentation of human beings can be wrong due to unintentional bias. This bias can happen for example; when a doctor’s efficacy towards a drug is involved in an experiment to see rather or not a drug is useful for patient treatment. “Open Intro statistics”, points out in a study with a control group a doctor may treat those he or she knows has been treated with the medicine with extra care, forging a difference in outcomes in the data, resulting in incorrect data. When evaluating human behavior, the integrity of results can become skewed due to what is called, “The Hawthorne Effect” which is common knowledge amongst aspiring Social Scientists. The Hawthorne effect came about when researchers stumbled on the fact when humans are being watched we are more productive or less likely to act in an undesirable way. Human behavior can change, and every person is different which can cause data to fluctuate.
Diez, D. M., Cetinkaya-Rundel, M., & Barr, C. D. (2017). Open Intro Statistics Third Edition.
Lumen. (2018). Lumen Boundless Sociology . Retrieved from Lumen Learning : https://courses.lumenlearning.com/boundless-sociol…