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1. When measuring a correlation, almost always there is no manipulation of the variables, the researcher is just simply analyzing how these 2 things interact naturally. So when describing the realationship as a positive correlation it would mean that these 2 variables are changing in a similar direction. Both values, x and y would be either increasing or decreasing together. A description of negative correlation means that the 2 variables change in opposite directions. As x increases, y decreases. An example of variables that seem to have a correlation is crime rates and climatic temperature.

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2. A positive correlation has two variables that are both moving along together meaning they either both increase at the same time or decrease at the same time. A negative correlation on the other hand has one variable that increases while the other variable decreases. An example of two variables that seem to be related but have nothing to do with each other is with height and weight. As we grow taller our weight tends to grow as well however they do not necessarily cause one another. A tall person can be the same weight as a shorter person and vise versa it just depends on the individual's overall health and anatomy.

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3. Hi Torie, I gave a similar example to yours. Mine was people having the need to drink something cold when the weather is hot, and also when the temperature is cold outside they need to be warm ,so their heating bills go up as a result. I have come to understand that in correlation two variables behave in the same way, they increase or decrease together. My great takeaway is knowing that there is no perfect correlation as variables do not have that kind of behavior ,and also when data is fine, irregular data could affect correlation that is why it is necessary to scrutinize data points for mistakes and keep the ones that belong. What was your key takeaway in this knowledge of correlations ? Looking forward to your reply . God bless:)

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4. After researching the correlations, some studies show many correlations that don't coincide with each other. It can be both the strong and weak side of correlation studies as some determine relationships among variables and others can't determine the variable because of the way it is perceived. It can be sort of complicated to evaluate correlations because of the significant positive correlation, however, it may not be strong. Most correlations show how the relationship between variables belong with one another.

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5. Thank you for sharing. I really enjoyed reading your post. It seems like you have the perfect understanding behind the whole concept of correlations. I struggled a little bit to understand it at the beginning, but reading more on examples of correlations really helped. It seems you got this statistics topic in your hands. Reading your post really helped me understand the cause and effect of correlations like their strengths and weaknesses. Good job.

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6. Strengths of correlations is that the variables seems to have numbers much more in common than usual, it can even be considered a coincidence. For example, the site shows the correlation between worldwide non-commercial space launches and sociology doctorates awarded. Between launces and degrees, both numbers we're on the same exact path. The weakness is that, variables sometimes do not make sense when correlating to others, such as the graph that showed drowning deaths and Nicholas Cage movies. Sometimes the variables can be unorthodox, which puts the correlation into questioning.