Definition: You are given a background paragraph that describes one or more causal or physical relationships, such as a relationship in economics, scientific law, or nature. You need to come up with a fictional story that makes use of the concepts or the relationship described in the provided paragraph. Make sure that your story does not repeat the relation in the given paragraph (e.g., by avoiding verbatim copies of the given paragraph). Start by reading the background paragraph, and determine what relationship(s) are in the paragraph. Write a story that involves the relationship(s) that you determined are in the background paragraph. Try to use your own words as much as possible and not repeat the background paragraph. Feel free to make up places and events as long as they tie back to the background paragraph in a way that you can ask a question about.

Positive Example 1 -
Input: Background Paragraph: A rise in price of a good or service almost always decreases the quantity demanded of that good or service. Conversely, a fall in price will increase the quantity demanded. When the price of a gallon of gasoline increases, for example, people look for ways to reduce their consumption by combining several errands, commuting by carpool or mass transit, or taking weekend or vacation trips closer to home. Economists call this inverse relationship between price and quantity demanded the law of demand. The law of demand assumes that all other variables that affect demand (which we explain in the next module) are held constant.
Output: The AAA auto club does a weekly report on the prices of gas and diesel in various cities. Historically, the prices have be fairly stagnant, but this week their report garnered widespread attention as the prices of gas and diesel plunged from last week in Seattle by $0.40 each. However, just across the border in Vancouver, the cost of gas went up dramatically by $0.50.

Positive Example 2 -
Input: Background Paragraph: The lesson is not that society is likely to make an extreme choice like devoting no resources to education at point A or no resources to health at point F. Instead, the lesson is that the gains from committing additional marginal resources to education depend on how much is already being spent. If on the one hand, very few resources are currently committed to education, then an increase in resources used can bring relatively large gains. On the other hand, if a large number of resources are already committed to education, then committing additional resources will bring relatively smaller gains.
Output: The state is deciding where to spend the rest of their budget for education. In an analysis of how districts in the state are spending their annual budgets, auditors found that in district A, most of the money was already being spent on schools. However, in district B, the money was not spent on school, but mostly on transportation.

Negative Example 1 -
Input: Background Paragraph: A rise in price of a good or service almost always decreases the quantity demanded of that good or service. Conversely, a fall in price will increase the quantity demanded. When the price of a gallon of gasoline increases, for example, people look for ways to reduce their consumption by combining several errands, commuting by carpool or mass transit, or taking weekend or vacation trips closer to home. Economists call this inverse relationship between price and quantity demanded the law of demand. The law of demand assumes that all other variables that affect demand (which we explain in the next module) are held constant.
Output: A rise in price of a good or service almost always decreases the quantity demanded of that good or service.

Now complete the following example -
Input: Background Paragraph: ANOVA generalizes to the study of the effects of multiple factors. When the experiment includes observations at all combinations of levels of each factor, it is termed factorial. Factorial experiments are more efficient than a series of single factor experiments and the efficiency grows as the number of factors increases.[45] Consequently, factorial designs are heavily used.
Output: 



Stories:
Medication A was tested on 1000 people for 3 years and cured Disease X in 80% of those trials. However,  Medication B was tested on 50 patients and cured Disease X in 90% of those trials.