• What are rival causes and when how should you look for them (what questions should you use to find them)?

Rival causes are alternative explanations for some event that occurred that also seem possible. Some questions to identify if there are rival causes is simply asking if there are any other possible explanations for the event that occurred. It is also all about taking a different viewpoint. You should try to put yourself in someone else’s shoes and see if there are any other causes.

• Explain the difference between causation and association/correlation. Which is more difficult to demonstrate and why

The basis of this difference is that we often oversimplify what is causing an event due to the causal oversimplification fallacy. We believe that if we find one thing that effects an event, that was the singular cause. There are many things that can be associated, but not be the main cause of it. For example, drug addiction is believed to be something that can be passed down genetically. So, some may mistakingly say that DNA is what causes addiction. However, that is just a small contributing factor. There is also exposure and behavior analytics that come into play. So DNA does not necessarily cause addiction, it is just associated with it.

• • • Conclusion: There is a higher rate of illness in college students
    • Reason/cause: College students do not sanitize living areas and common areas
    • Rival (other possible) causes: They do not have the money to buy preventative medicine, they do not have a well-balanced diet to support the immune system, they are living closer to other people than people who are not in college
    • Evaluation (How strong is the original argument? What’s missing?): I think that the argument is valid, but even if the living areas had more germs, washing hands would eliminate this factor. There is nothing saying that college students don’t wash their hands or use proper personal hygiene.

B. Based on your reading of ARQ chapter 10, “Are Any Statistics Deceptive?”, summarize how the following types of statistics can be deceptive. What are some strategies you can use to determine how reliable each type is?

• Unknowable and biased statistics

This is when large numbers are used to strike curiosity and shock. For example, it will make more people listen to you if you say that 90% of people they know are carrying corona virus, rather than saying it is possible that 30% of the people you know may have been exposed. To decide how reliable it is, further research needs to be done into how these statistics were obtained and if there is other supporting evidence for their numbers.

• Confusing averages

Average is a very vague term to explain a subset of ways to get data. Average can be mean using the mean, median, or mode. Depending which one you use, it will change how high or low your statistic is. This can be used by “researchers” to skew the data to match their hypothesis. To determine how reliable it is, you want to see if they provide raw statistics that show what the different kinds of averages look like compared to each other.

• Measurement errors

When making a claim, there can be errors in obtaining the data. If the measurements are off, then the conclusion could be incorrect. A way to determine how reliable this is, would be to use critical analysis and decide if there are any possible issues that could have occurred during the obtaining of data. See if these issues are addressed in the research.

• Concluding one thing, proving another

This is when the statistic itself says one thing, but the conclusion is not answering that same question. In order to decide if a statistic is reliable, you need to be able to take a step back and ask what the statistic itself is saying. Then, look at the conclusion and see what that is answering. Compare the two conclusions and see if they are similar.

Deceiving by omitting information

This is when certain information is not mentioned in order to make the statistic sound more impressive. To decide if a statistic is omitting information, there are two variables to look for: absolute numbers and percentages. A statistic will be more reliable if both absolute numbers and percentages are given. This will show the true gravity of the statistic.

C. Read the following passage. Identify the conclusion, and reasons, and evaluate the evidence (in this case the statistics) used to support the writer’s argument.

The home is becoming a more dangerous place to spend time. The number of home-related injuries is on the rise. In 2005, approximately 2300 children aged 14 and under died from accidents in the home. Also, 4.7 million people are bitten by dogs each year. To make matters worse, even television, a relatively safe household appliance, is becoming dangerous. In fact, 42,000 people are injured by televisions and television stands each year. With so many accidents in the home, perhaps people need to start spending more time outdoors.

• • Conclusion: The home is becoming a dangerous place to spend time, so more people should go outdoors.
  • Reasons/causes: The home-related injuries is rising due to dogs, TVs, and children are dying from accidents in the home.
  • Evaluate the evidence (the statistics): I don’t find these statistics to be particularly reliable. First off, it seems that they are omitting information. They give absolute numbers, but don’t tell us what percentage of people that is. So, it makes it hard to understand how much of an issue this is. For example, it may be true that 42,000 people get injured by TV accidents, but that is what percentage of people who own a TV. Also, it claims that there is a “rise” in home-related injuries, but gives us no other statistical time frames to relate these statistics to.