Negative and Positive Correlation: What Does It Mean?

Correlation is the process of including and comparing different variables with similar attributes. There are two types, negative and positive correlations. While the positive correlation is where two variables vary directly, the negative correlation is where the value of two variables varies inversely. Part 6 highlights my survey and poll results on the prevalence of cancer among USA citizens. It shows different variables ranging from age to the number of people in that age group that have been diagnosed with cancer. This data analysis can make a different conclusion in relation to the research. For instance, we can conclude that prevalence and age were correlated positively. We can so concur that the research analysis shows that majority of Americans at a young age are not prone to cancer. We can also conclude that the value of one variable is greatly dependent on how the second variable is placed. Another conclusion is that on the negative correlation, a relationship has been inverted where an increase will trigger a corresponding decrease. There are a couple of confounding factors in these results. It is surprising that the prevalence of cancer rises relatively to age until the age group of 57 and drops significantly as the age group rises. According to a claim sighted in part five, it is confounding that people who exercise regularly are more prone to cancerous infections (DeSantis et al., 2019). This argument is supported by scientists who say that exposure to direct sunlight increases the chance of the body developing cancerous cells. I feel like I covered all areas in my analysis, especially with the poll and survey. The hypotheses in the phase are valid and relevant and cover all the areas. However, I feel like there are questions that would have asked better and elaborate better. If the paper had more hypothetical questions like what age group is more prone to cancer cells? What are the leading causes of cancer? What are some of the variables in the myths and misconceptions about cancer that have been circulating? How manageable and treatable is cancer? Providing answers to these questions sequentially would shed more light on the chosen topic and enable the reader to understand the survey and the research more. One of the limitations of my study was the lack of a good hypothesis. Reasonable hypotheses would help improve the flow of the analysis. I also provided just one survey containing just two variables which are the age group and the number. I feel like there was still room for more variables. A pie chart or a more visual data representation for the poll or survey would have been appealing to the eyes, for example, a pie chart or a graph that shows more variables ( Duquia et al., 2014). Another limitation is the lack of more reference sources. The sources sighted are minimal and, in some cases, not very clear. More sources would have provided precise information and more clarity on the topic. For instance, more references on cancer would give more insights on this topic. The population sampled was only a mid-groupage, and this is very general. While narrowing it down to specific ages would have increased the size of the sample population, it would give more accurate data. Lastly, I feel like if the limitations are rectified, then the study will be perfect. Increased scrutiny of the details of reference sources, the representation of data in a more visually attractive way, and increasing the ample population size will be the proper places to start. As I prepare the survey, it would be wise to have specific ages rather than the age groups as used previously in part. 

References 

DeSantis, C., Miller, K., Dale, W., Mohile, S., Cohen, H., & Leach, C. et al. (2019). Cancer statistics for adults aged 85 years and older, 2019.  CA: A Cancer Journal For Clinicians ,  69 (6), 452-467. https://doi.org/10.3322/caac.21577 

Duquia, R. P., Bastos, J. L., Bonamigo, R. R., González-Chica, D. A., & Martínez-Mesa, J. (2014). Presenting data in tables and charts. Anais brasileiros de dermatologia , 89 , 280-285.