The Nature of Statistics
We'll try to ease the 'patience' part here as much as possible.
As you may have noticed, statistics is perhaps the most common way of presenting relationships between worldly entities, ranging from substances to certain behavioral trends. It is a collection of numbers that tell you that coffee is good for you while demonstrating that it can also lead to all sorts of health problems in one way or another.
So what roles does statistics play in the relationship between correlation and causation?
Statistics is essentially a way of showing a quantitative pattern between factors (also known as variables) of interest. When the collected data is plotted against graphs, one may analyze the graph via tools such as the correlation coefficient to determine connections and patterns. However, as some humorous examples may show, some apparent 'connections' or 'similarities' may not have any concrete implications. Remember that graphs, in a sense, is a visual representation.
Thus, one can reach the conclusion that it is not the mere 'picture' offered by statistics that matters, but the way we interpret the picture that counts. It is worth noting that a phenomenon may need both qualitative and quantitative explanation. The more we add to the interpretation, the better results we will reap. Furthermore, the quality and the characteristics of the sample group which serves as the basis of the statistics also matters.
Here is a list of websites that offer other useful insights.
So what roles does statistics play in the relationship between correlation and causation?
Statistics is essentially a way of showing a quantitative pattern between factors (also known as variables) of interest. When the collected data is plotted against graphs, one may analyze the graph via tools such as the correlation coefficient to determine connections and patterns. However, as some humorous examples may show, some apparent 'connections' or 'similarities' may not have any concrete implications. Remember that graphs, in a sense, is a visual representation.
Thus, one can reach the conclusion that it is not the mere 'picture' offered by statistics that matters, but the way we interpret the picture that counts. It is worth noting that a phenomenon may need both qualitative and quantitative explanation. The more we add to the interpretation, the better results we will reap. Furthermore, the quality and the characteristics of the sample group which serves as the basis of the statistics also matters.
Here is a list of websites that offer other useful insights.