Capella University Numerical

read Chapter 8 in the course textbook and

review the Correlation Doesn’t Equal Causation: Crash Course Statistics #8 (Links to an external site.) and The Danger of Mixing Up Causality and Correlation: Ionica Smeets at TEDxDelft (Links to an external site.) videos.

In this post, you will be challenged to look at how statistical tests, such as correlation, are commonly used and the possible limitations of such analyses. Additionally, you will need to explain statistical concepts; accurately interpret results of statistical tests; and assess assumptions, limitations, and implications associated with statistical tests.

  • Much has been written about the relationship between students’ SAT test scores and their family’s income. Generally speaking, there is a strong positive correlation between income and SAT scores. Consider and discuss the following questions as you respond:
  • What does this correlation tell you?

Is this correlation evidence that having a high family income causes one to have high SAT scores?

Is this correlation evidence that high SAT scores cause higher income? Or does this tell you something else? Explain your answer.

Explain why correlation alone is rarely sufficient to demonstrate cause.

Provide a personal example of two variables that may be correlated but not have a cause and effect relationship. Identify what type of bivariate correlation is involved, based on the measurement scales of the variables.

  • Peer 1 

Hello Class and Professor,

  For this week discussion I found that in order to make a correlation you must “make a distinction between correlation and cause” (Tanner, D. (2016) Sec.8.1) for the topic of if there is a correlation between income and SAT scores is that due to the low scores that are presented are  displayed in lower income or poverty homes. The low scores of kids are of those that have a low social class as the correlation.

  •         I do believe that this correlation is evident that having a high family income causes one to have high SAT scores. I am sure there will be a positive correlation between lower test scores when compared to family social class or income has the ability to have and the relationship is based on scores verses social class
  • Is this correlation evidence that high SAT scores cause higher income?
  •            The correlation is evident due to the strong correlation of household incomes that are lower have low test scores are likely to have similar data of correlation as well. The linear relationship displays that “they don’t have to be the same” (Crash Course. (2018, March 14) variables or similar to have correlation. Evident that the correlation stem from low scores in lower class areas.
  • Explain why correlation alone is rarely sufficient to demonstrate cause.
  •         Correlation alone is not sufficient to demonstrate for a cause due to needing 2 variables to have similar data numbers. The variables do not have to be similar or the same. The strong correlation is dependent on the variables that has similar data. Determining if the distinction has cause to evaluate plays a part in determining correlation as well. In the case of this week discussion the data could display correlation in the variables.

Provide a personal example of two variables that may be correlated but not have a cause and effect relationship. Identify what type of bivariate correlation is involved, based on the measurement scales of the variables.

           An example could be the number of Lawn mowers sold in the winter in correlation to the amount of individual that work outside in the winter. This correlation example is two numerical bivariate correlation of data.

Peer 2 

Hello Everyone, 

What does this correlation tell you?

This correlation between family incomes and it’s association with a student’s SAT scores, suggest that there is a positive correlation between the two, and that it can impact whether a student receives a higher score. This could be due to the fact that families with higher incomes can afford all the tools such as tutors and SAT prep courses, to ensure their student succeeds. 

Is this correlation evidence that having a high family income causes one to have high SAT scores?

In my opinion having a higher income does not mean the student will always achieve a high SAT scores. Although there is a correlation between income and SAT scores, it does not show real evidence that a family having a higher income will guarantee a higher score. 

Is this correlation evidence that high SAT scores cause higher income? Or does this tell you something else? Explain your answer.

A student who has the resources has a higher chance of achieving a a high SAT score. However, this does not show that a student with a family of lower income and not as many academic opportunities, can not succeed at the same level. The research provided however, is not clear on whether this one mean a higher SAT score, has a direct correlation with a higher income. One can assume though, if a student achieves high SAT scores, attends a fine academic institution, and receives a college degree, they have a chance of getting a more higher paid career position. 

Explain why correlation alone is rarely sufficient to demonstrate cause.

With correlations we are able to see how two or variables can impact causes and effects of one another. However, just because two variables occur together, does not mean there will be a direct correlation. 

Provide a personal example of two variables that may be correlated but not have a cause and effect relationship. Identify what type of bivariate correlation is involved, based on the measurement scales of the variables.

An example of two variables that could be correlated but may not necessarily have a cause and effect would be the amount of classes missed of a semester course, to the score a student receives on a final exam. Although we may assume if a student missed several days they will not score well on their final exam, that correlation is not set in stone. 

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