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Respond to... I was able to find a study that is set to see if there is any effect on the amount of alcohol consumed by one that is viewing a movie when an actor/characters in the film is portrayed us
Respond to...
I was able to find a study that is set to see if there is any effect on the amount of alcohol consumed by one that is viewing a movie when an actor/characters in the film is portrayed using is the I have always been a big movie buff add that to my undergrad in social science, one can see why I picked the study that I did. This study was done by dividing 122 young adults ages 18 to 29 into smaller groups by sex. The then got to watch movies in a simulated living room and where of course offered drinks. The amount that each participant consumed got record. Half of the participants watched films in which the actors/characters use alcohol and half had films where they did not use the substance. I don’t know if this is the most straightforward of an example of quantitative analysis since some of the data is qualitive, however I feel that enough quantitative data is used to justify using this study as my example.
Because of the number of variables that are being analyzed, the researchers chose to use a multivariate regression analysis to interpret and read the data. Multivariate regression analysis is used when researchers need to look at the relationship between multicable variables. By doing this, researchers can see if different variables change outcomes. This study was able to determine a trend that when males who watched films in which alcohol is used, they tended to drink more than if they had been waiting a film without it being used. Female participants showed no differences in consumption rate between the two types of films.
Koordeman, R., Anschutz, D. J., van Baaren, R. B., & Engels, R. C. M. E. (2011). Effects of alcohol portrayals in movies on actual alcohol consumption: an observational experimental study. Addiction, 106(3), 547–554. https://doi-org.proxy-library.ashford.edu/10.1111/j.1360-0443.2010.03224.x
https://stats.idre.ucla.edu/stata/dae/multivariate-regression-analysis/
Respond to...
Locate an example of a research study that uses quantitative analysis. Explain what this statistical method allowed the researchers to accomplish and conclude in the study.
Heart Rate Variability (HRV) has been a growing global health concern worldwide. It’s a key factor to determine an individual’s cardiovascular condition. The imbalance in the heart rate has profound impact in causation of several heart diseases. This study aimed to investigate the HRV risk factors that are predominant in the development of heart diseases in motorbike riders. In the Heart Rate Variability study with motorbikes, the quantitative method that was used is the descriptive design. The descriptive design describes the current status of a variable. There is no hypothesis at the beginning of the study. Once all the data is collected which is mostly in observation, then the hypothesis is developed. The descriptive method allowed the research study to look at how the variables of the different motorbikes affected the ten healthy subjects (Ramasamy, Adalarasu, & Patel, 2018). The pulse oximeter was taken before, during, and after the motorbike riding (Ramasamy, Adalarasu, & Patel, 2018). The difference of the pulse oximeters in the five different motorbikes leads to their conclusion of the study (Ramasamy, Adalarasu, & Patel, 2018). The heart rate variability is a growing concern across the globe (Ramasamy, Adalarasu, & Patel, 2018). The heart rate imbalance can have an impact on several heart diseases (Ramasamy, Adalarasu, & Patel, 2018). The study concluded that the heavier weights of the motorbike, the more risk of heart rate variability (Ramasamy, Adalarasu, & Patel, 2018). When on a motorbike there is also vibration to the body which in turns causes risk to the heart rate variability (Ramasamy, Adalarasu, & Patel, 2018). The speed of the motorbike also affects the heart rate variability (Ramasamy, Adalarasu, & Patel, 2018). There are some other factors discovered that also have an impact on the heart rate variability such as wheel dimension, body design, and vehicle suspension (Ramasamy, Adalarasu, & Patel, 2018). All the factors can be and are quantified which results in the statistical method of quantitative analysis. The research using quantitative analysis can help prove that there needs to be ergonomic interventions to motorbikes to help decrease the heart rate variability risk (Ramasamy, Adalarasu, & Patel, 2018).
References
Ramasamy, S., Adalarasu, K., & Patel, T. N. (2018). Quantitative analysis of heart rate variability exposures in motorbike riders. Biomedical Research (India), 29(10), 2078-2082. Retrieved from https://pdfs.semanticscholar.org/c300/49bad93c7dac28a4d3e7e09d5ee1c0377abb.pdf
