few_shots: Example:
Problem/activity:
Stage 1: Money
Required Preparation
Materials to Copy
Blackline Masters
Would You Rather Stage 1 Spinner
Would You Rather Stage 1 Recording Sheet

Narrative
The first partner spins to get a group of coins. They write a question that compares the amount they spun to a different group of coins that they make up.


Mathematical concept/skill options: 
A. Solve problems involving measurement and estimation of intervals of time, liquid volumes, and masses of objects.
B. Represent and interpret data.
C. Geometric measurement: understand concepts of volume and relate volume to multiplication and to addition.
D. Geometric measurement: recognize perimeter as an attribute of plane figures and distinguish between linear and area measures.
E. Describe and compare measurable attributes.
F. Geometric measurement: understand concepts of angle and measure angles.
G. Convert like measurement units within a given measurement system.
H. Geometric measurement: understand concepts of area and relate area to multiplication and to addition.
I. Measure and estimate lengths in standard units.
J. Classify objects and count the number of objects in each category.
K. Tell and write time.
L. Solve problems involving measurement and conversion of measurements from a larger unit to a smaller unit.
M. Measure lengths indirectly and by iterating length units.
N. Work with time and money.
O. Relate addition and subtraction to length.


Your response:
{
  "explanation": "In this problem, students work with money in the form of coins.",
  "answer": "N"
}

Now, assign the following problem or activity to one or more relevant mathematical concepts/skills it teaches.
shot_info: im_center_000269

2
options: Understand and evaluate random processes underlying statistical experiments.

Use the rules of probability to compute probabilities of compound events in a uniform probability model.

Use random sampling to draw inferences about a population.

Use probability to evaluate outcomes of decisions.

Investigate patterns of association in bivariate data.

Interpret linear models.

Summarize, represent, and interpret data on two categorical and quantitative variables.

Investigate chance processes and develop, use, and evaluate probability models.

Develop understanding of statistical variability.

Calculate expected values and use them to solve problems.

Summarize, represent, and interpret data on a single count or measurement variable.

Draw informal comparative inferences about two populations.

Make inferences and justify conclusions from sample surveys, experiments, and observational studies.

Understand independence and conditional probability and use them to interpret data.

Summarize and describe distributions.
problem_activity: Task
Many counties in the United States are governed by a county council. At public county council meetings, county residents are usually allowed to bring up issues of concern. At a recent public County Council meeting, one resident expressed concern that 3 new coffee shops from a popular coffee shop chain were planning to open in the county, and the resident believed that this would create an increase in property crimes in the county. (Property crimes include burglary, larceny-theft, motor vehicle theft, and arson -- From http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2010/crime-in-the-u.s.-2010/property-crime accessed on December 5, 2012.)
To support this claim, the resident presented the following data and scatterplot (with the least-squares line shown) for 8 counties in the state:
{"table": [{"_attributes": {"class": ["centered", "narrow"]}, "tbody": [{"tr": [{"th": [{"_value": "County"}, {"_value": "Shops"}, {"_value": "Crimes"}]}, {"td": [{"_value": "A"}, {"_value": "9"}, {"_value": "4000"}]}, {"td": [{"_value": "B"}, {"_value": "1"}, {"_value": "2700"}]}, {"td": [{"_value": "C"}, {"_value": "0"}, {"_value": "500"}]}, {"td": [{"_value": "D"}, {"_value": "6"}, {"_value": "4200"}]}, {"td": [{"_value": "E"}, {"_value": "15"}, {"_value": "6800"}]}, {"td": [{"_value": "F"}, {"_value": "50"}, {"_value": "20800"}]}, {"td": [{"_value": "G"}, {"_value": "5"}, {"_value": "2800"}]}, {"td": [{"_value": "H"}, {"_value": "24"}, {"_value": "15400"}]}]}]}]}
[IMG]
The scatterplot shows a positive linear relationship between "Shops" (the number of coffee shops of this coffee shop chain in the county) and "Crimes" (the number of annual property crimes for the county). In other words, counties with more of these coffee shops tend to have more property crimes annually.
Does the relationship between Shops and Crimes appear to be linear? Would you consider the relationship between Shops and Crimes to be strong, moderate, or weak?
Compute the correlation coefficient.  Does the value of the correlation coefficient support your choice in part (a)? Explain.
The equation of the least-squares line for these data is:
$$ \text{Predicted Crimes} = 1434 + 415.7 \text{(Shops)} $$
Based on this line, what is the estimated number of additional annual property crimes for a given county that has 3 more coffee shops than another county?
Do these data support the claim that building 3 additional coffee shops will necessarily cause an increase in property crimes?  What other variables might explain the positive relationship between the number of coffee shops for this coffee shop chain and the number of annual property crimes for these counties?
If the following two counties were added to the data set, would you still consider using a line to model the relationship? If not, what other types (forms) of model would you consider?
{"table": [{"_attributes": {"class": ["centered", "narrow"]}, "tbody": [{"tr": [{"th": [{"_value": "County"}, {"_value": "Shops"}, {"_value": "Crimes"}]}, {"td": [{"_value": "I"}, {"_value": "25"}, {"_value": "36900"}]}, {"td": [{"_value": "J"}, {"_value": "27"}, {"_value": "24100"}]}]}]}]}


correct_option_index: 5

6