few_shots: 
Example:
Problem/activity:
You’re mixing ingredients for cookies. The recipe says to combine 6 tablespoons, or ¾ stick, of butter with 1 cup of sugar. You accidentally mix in a whole stick of butter (8 tablespoons) with the cup of sugar. How can you fix this?


Description: 
Use ratio and rate reasoning to solve real-world and mathematical problems, e.g., by reasoning about tables of equivalent ratios, tape diagrams, double number line diagrams, or equations.

Answer: 
Yes. This problem solves a real-world problem involving mixing ingredients for cookies. A student doing this problem would need to reason about equivalent ratios of butter amounts to sugar amounts.

Now, assess whether the following problem or activity aligns with the provided description.

shot_info: fl_problem_000972_pos_0

6
standard_description: Solve simple rational and radical equations in one variable, and give examples showing how extraneous solutions may arise.
problem_activity: Task
Below is a table showing the approximate boiling point of water at different elevations:
{"table": [{"_attributes": {"class": ["regular"]}, "tbody": [{"tr": [{"th": [{"_value": "Elevation (meters above sea level)"}, {"_value": "Boiling Point (degrees Celsius)"}]}, {"td": [{"_value": "0"}, {"_value": "100"}]}, {"td": [{"_value": "500"}, {"_value": "98.2"}]}, {"td": [{"_value": "1000"}, {"_value": "96.5"}]}, {"td": [{"_value": "1500"}, {"_value": "94.7"}]}, {"td": [{"_value": "2000"}, {"_value": "93.1"}]}, {"td": [{"_value": "2500"}, {"_value": "91.3"}]}]}]}]}
Based on the table,
if we were to model the relationship between the elevation and the boiling point of water, would a linear function be appropriate? Explain why or why not.
Below are some additional values for the boiling point of water at higher elevations:
{"table": [{"_attributes": {"class": ["regular"]}, "tbody": [{"tr": [{"th": [{"_value": "Elevation (meters above sea level)"}, {"_value": "Boiling Point (degrees Celsius)"}]}, {"td": [{"_value": "5,000"}, {"_value": "83.2"}]}, {"td": [{"_value": "6,000"}, {"_value": "80.3"}]}, {"td": [{"_value": "7,000"}, {"_value": "77.2"}]}, {"td": [{"_value": "8,000"}, {"_value": "74.3"}]}, {"td": [{"_value": "9,000"}, {"_value": "71.5"}]}]}]}]}
Based on the table,
if we were to model the relationship between the elevation and the boiling point of water, would a linear function be appropriate? Explain why or why not.
When the information from both tables is combined, would a linear function be appropriate to model this data?  What kind of function would you use to model the data?  Why?


aligns: no