RESPOND TO THESE COMMENTS BY EXPRESSING OPINION AND SUGGESTION.

1)Correlation is a relationship between two variables. Whereas, causation is a cause and effect relationship. However, correlation is not causation. For example, just because people spend more money shopping when it is cold out, rather than hot, does not mean colder weather causes high spending. Another example of correlation without causation is the amount of shark attacks and ice cream sales. Although these variables show correlation, one does not cause the other.

After creating the scatterplot and calculating R value (correlation) for the data of fertility rates and life expectancy, 66.4% of the changes in life expectancy are explained by changes in fertility rates. The R value (correlation) is -0.81459, meaning the variables are 81.5% negatively correlated. Therefore, if fertility rates decrease, life expectancy will increase.

2)Causation means a relationship is seen between variables, where one is directly causing the other to happen. Correlation also means there is a relationship observed between variables, but neither is necessarily causing the other.

One example of correlation without causation would be someone believing that the reason they've never been in a car accident is because every time before they drive they knock on wood.

The r value of the data is -0.815, and the r^2 value is .664. This shows the variables are negatively associated, and that for every extra child, life expectancy drops 4.66 years from a starting point of 86.1.

This is not necessarily causation because there could be countless lurking variables, especially when comparing things globally. Differences in culture and lifestyle make direct comparison of a single variable on such a scale extremely difficult. Richer countries also tend to have fewer children, which may have nothing to do with health and will affect the results. The life expectancy could be due to unrelated things such as medical treatment and access, education, nutrition, wealth, sanitation, lifestyle, etc. This is correlation with many lurking variables explaining the relation.

The two variables studied do not directly cause the other, unless maybe death due to childbirth is much more common in cultures that have more children. That would affect the average life expectancy, but not the individual life expectancy in the way the study suggests.