Answer:
The conclusion is false, because it is assuming that correlation = causation.
Explanation:
An important principle in statistical analysis is the principle that when correlation exist between two variables or more, it does not mean that one of the variables are causing the other to appear in a certain manner.
Remember that correlation means that you are investigating whether a relationships exists between two variables; in this example, as we can see, it is between the biodiversity in an ecosystem and the population of an insect.
The graph can be said to illustrate the result of the research; that as the biodiversity of the ecosystem goes down, the insect's population goes up. This is a form of negative correlation.
However - we do not know what is the direction of the relationship; the student concludes that as some insects die within the ecosystem, the researched insect's population goes up; assuming that the predator species died off and thus the researched insect's population increases.
Yet, it is also possible for the relationship to go towards the other direction; the researched insect population increases - perhaps by the introduction of a new food source that causes the species' population to increase - and thus, this damages the biodiversity of the ecosystem, making the population go down since it is possible that the researched insect is instead the species which is on top of the food chain at that ecosystem.
To investigate the direction of a relationship, further research need to be done and more sophisticated statistical methods need to be used.
