The second mistake students make is confusing causes and reasons. Students need to avoid broad topics like these. Instead of an in-depth analysis, the essay is shallow and rushed. ![]() These topics provide too much information to cover in a short paper. Books have been written about topics like this. One mistake students make is to pick a topic that is too broad for example, students choose topics like the causes of climate change or the effects of the Great Depression. Students make a few mistakes when choosing a topic. These topics are focused enough to provide sufficient information to complete a three to four page essay with in-depth analysis of the topic and support from outside sources. In other words, x most definitely causes y, or y is a direct result of x. These topics identify clear cause/effect relationships. Effects of air pollution on inner-city children.The topic needs to cover a true cause/effect relationship. First, they struggle to identify an appropriate topic. Many students find the causal analysis essay hard to write. They will read and assimilate the information, then incorporate it in their work as evidence and support. With the causal analysis, students will be expected to identify credible sources for their papers. If 90% of the papers students will write in college are in third person, 98% of the papers will be source-based. With the causal analysis essay, students are introduced to source-based writing. These are just a couple of ways that causal analysis is utilized in society, so it is important to be able to understand it. Then they provide the probable effects of the train system on the valley based upon similar results from other cities. ![]() What caused it? When deciding to spend all of that taxpayer money to build the train system in the valley, supporters first gather data showing the current effects of all of the traffic on the city. ![]() When studying accidents or plane crashes, investigators attempt to determine the sequence of events that led to the crash. \)Ĭausal analysis, or cause and effect, is used in both everyday and professional life, so being able to recognize and incorporate cause/effect data is important as it is used in multiple applications including problem solving.
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