Analyzing Correlation and Causation

Concepts of Correlation and Causation

Task:

Discussion question incomplete. Missing the scatterplot Graph and the correlation coefficient, Total Variation, Standard issue, ect.. (I must have two quantitative variables to perform a correlation calculation. Your variables of having diabetes and heat disease are not quantitative. A quantitative variable must be an objective, numerical measurement. You might look at the exercises at the end of section 7.1 in the textbook for ideas, but don't use one of them) I've attached my Discussion Answer (Word.doc) I just need it to have the correlation calculation to match my discussion answer.. Also Below is the Original Discussion Question If you want to come up with something completely new that's okay too But I still need the graph and calculations as well.. (At least 2-paragraphs/Graph & correlations and calculations Analyzing Correlation and Causation This week's Introduction about ice cream sales and crime rates was an example of correlation being mistaken for causation. In this Discussion, you will identify and analyze a real-world correlation and decide whether it truly shows causation. To prepare for this Discussion: Review the Concepts and Applications exercises on pages 319–320 of your text, where you will find several problems describing real-life examples of correlation and causation. Think about how you might respond to the questions posed. Think about what real-life situations you have noticed that might show a correlation between two things. Perhaps it's a relationship between two events you've observed. Or maybe you read online or in a newspaper that as one thing changes, so does another. Determine whether the correlation is positive or negative. Describe how someone might infer that one event "causes" the other. Decide if this causation is reasonable, or if there is another explanation for why the two events are correlated. How might you decide, using scientific methods, whether one variable actually causes the other to occur? Reference: Chapter pager attached)

Despite confusion between correlation and causation, the two entities refer to different meanings. Correlation is a measure in statistics, which evaluates the size and direction of a relationship between a single, or more variables. On the other hand, causation is an indication that an event results from the occurrence of the other. As such, there is a causal relationship between the two events (Cohen, West, & Aiken, 2014). At times this is referred to as the cause and effect. There are numerous problems, which describe correlation and causation from a real-life situation.

Correlation is measured by using correlation coefficients — coefficient numerical range from a positive one to a negative one, including zero. Hence, correlation can be described as positive or negative. When there is no correlation, 0 is the variable used. On the other hand, causality is established by the use of the control method. A sample or population is split into two, and both can be compared in every way. In most cases, a correlation is first established, then causality is serviced from the coefficients. Smoking and lung cancer have been debated so much n the past decade (de Vos, & de Vos, 2012). There is a positive correlation between lung cancer and tobacco smoking. Since tobacco has chemicals, which affect the lungs, they cause a person to acquire certain viruses, which cause cancer. The idea of tobacco causing cancer makes that a reasonable causality. However, lung cancer can be caused by different other entities. in this case, the two being studied events concern tobacco and lung cancer. Also, a cause and effect is being noticed from the variables provided.