Please read the discussions and respond to them with reference
Correlation is a statistical technique that is used to measure and describe the STRENGTH and DIRECTION of the relationship between two variables.
Correlation requires two scores from the SAME individuals. These scores are normally identified as X and Y. The pairs of scores can be listed in a table or presented in a scatterplot. Usually the two variables are observed, not manipulated.
The error in this correlation is that there needs to be more data to determine that there are no other factors involved that could cause the heart rate to increase besides just cigarettes.
Statistics Solutions. (2018). Correlation. Retrieved from http://www.statisticssolutions.com/correlation-pea…
When I look up the definition of linear correlation I find the following:
1. mutual relation of two or more things, parts, etc.
2. the act of correlating or the state of being correlated.
3. (in statistics) the degree to which two or more attributes or measurementson the same group of elements show a tendency to vary together.
So i believe we could stipulate that there could be a correlation between the cigarettes and the pulse rate but i think we would eed more data to say specifically that one influenced the other. I am sure that the pulse rate would go up with nicotene but is there other things involved. Did the person have caffeine recently? Is there outside stress? What meds are they on? Just some of the examples of things that also could be influencing the pulse rate.
Random House Kernerman Webster’s College Dictionary, Â© 2010 K Dictionaries Ltd. Copyright 2005, 1997, 1991 by Random House, Inc. All rights reserved.
The assumption is that cigarettes alone are one variable that is causing the increased heart rate. There are many factors that can contribute to an elevated heart rate besides cigarette use, there are other attributing factors like caffeine, chocolate, AF, fight or flight syndrome to name a few. With statistics there needs to be an x and y for the comparison of the data. To make a null hypothesis without any data to back it up is in error. The study needs a theoretical framework to give it validity. Otherwise this is like politics where I can make any statement that supports a theory of mine but there is no data to back it up and therefore I will not have any validity with the next statement that I release to the press. That would be the beauty behind science and statistics that there is a study that has been validated with a study that shows our results that either prove the null hypothesis or cause the rejection and thereby a new study established.
Grove, S. &. (2017). Statistics for Nursing Research: A Workbook for Evidence-Based Practice. St. Louis: Elsevier, pp. 236.
Correlation is used in statistical analysis to determine the type and extent of a relationship between two variables (Lecture 5, 2013). Although we may be able to see a correlation between two variables, we cannot make a conclusion without further evidence. The error occurs in the given example because correlation does not exactly imply causation. There could be many other variables affecting the pulse rate that are not listed. For example, the person could be super stressed, causing him/her to smoke more cigarettes and at the same time running around at a fast pace trying to complete tasks/errands. We would need to gather more information in order to directly correlate cigarettes to an increased pulse rate.
Lecture 5 (2013). HLT-362v: Applied Statistics for Health Care Professionals. Phoenix, AZ: Grand Canyon University
As it states in our Week 5 lecture, correlation does not mean cause and effect. The error here is the assumption that pulse rate and amount of cigrettes are mutually exclusive. The error would be to ignore other factors that could increase the heart rate of the participants. What kind of stress do they have going on in their lives, what did they eat that day, how was their water intake that day. There are so many other variables that could cause one’s heart rate to increase. Could there be a correlation, sure, but there is no evidence that that is the main cause.
The error in this conclusion is the lack of information provided. What was the study size? How many times was this tested? How many cigarrettes were smoked in a row to provide this conclusion, and was this a controlled study? Was caffeine ever drank while the user was smoking? More information is necessary in order to verify the validity of this study. For all we know based on the information provided, this could have been one person monitoring his heart rate while smoking, and because he had an elevated heart rate, he came to this conclusion.