Determine whether the following statement makes sense or does not make sense, and explain your reasoning:
By modeling attitudes of college freshmen from 1969 through 2006, I can make precise predictions about the attitudes of the freshman class of 2020.
A) This makes sense because you can fit a function to the data on attitudes of college freshmen and then use that model to predict the attitudes of future classes.
B) This does not make sense because even though mathematical models provide excellent estimates about future attitudes, they cannot guarantee perfect precision.
I'll be glad to comment on your answer.
I think its A because there can be a function to the data.
I disagree. No mathematical model can exactly predict the future with perfect precision.
Experts have made many bad predictions.
http://www.rinkworks.com/said/predictions.shtml
B) This does not make sense because even though mathematical models provide excellent estimates about future attitudes, they cannot guarantee perfect precision.
To determine whether the statement makes sense or not, we need to analyze the reasoning behind it. The statement suggests that by modeling attitudes of college freshmen from 1969 through 2006, one can make precise predictions about the attitudes of the freshman class of 2020.
Option A suggests that it makes sense because a function can be fitted to the data on attitudes of college freshmen, and that model can be used to make predictions about future classes. This is a valid interpretation, as statistical models can be used to estimate trends and patterns from past data and apply them to make predictions about the future. However, it is important to note that these predictions are not guaranteed to be precise because there are numerous variables and complexities that can influence attitudes in different time periods.
Option B provides the correct reasoning by stating that mathematical models can provide excellent estimates about future attitudes, but they cannot guarantee perfect precision. This acknowledges the limitations of modeling and prediction, which are influenced by various factors such as changes in social, cultural, and technological aspects over time.
Therefore, the statement does not make sense because while modeling can estimate future attitudes, it cannot provide precise predictions due to the inherent uncertainties and variations that exist.