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?


Standard options: 
A. Understand the concept of a ratio and use ratio language to describe a ratio relationship between two quantities. For example, “The ratio of wings to beaks in the bird house at the zoo was 2:1, because for every 2 wings there was 1 beak.” “For every vote candidate A received, candidate C received nearly three votes.”
B. 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.
C. Understand the concept of a unit rate a/b associated with a ratio a:b with b ≠0, and use rate language in the context of a ratio relationship. For example, “This recipe has a ratio of 3 cups of flour to 4 cups of sugar, so there is 3/4 cup of flour for each cup of sugar.” “We paid $75 for 15 hamburgers, which is a rate of $5 per hamburger.” (Expectations for unit rates in this grade are limited to non-complex fractions.)


Your response:
{
  "explanation": "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.",
  "answer": "B"
}

Now, assign the following problem or activity to one or more relevant standards it aligns with.
shot_info: fl_problem_000972

6
options: Understand that patterns of association can also be seen in bivariate categorical data by displaying frequencies and relative frequencies in a two-way table. Construct and interpret a two-way table summarizing data on two categorical variables collected from the same subjects. Use relative frequencies calculated for rows or columns to describe possible association between the two variables. For example, collect data from students in your class on whether or not they have a curfew on school nights and whether or not they have assigned chores at home. Is there evidence that those who have a curfew also tend to have chores?

Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association.

Use the equation of a linear model to solve problems in the context of bivariate measurement data, interpreting the slope and intercept. For example, in a linear model for a biology experiment, interpret a slope of 1.5 cm/hr as meaning that an additional hour of sunlight each day is associated with an additional 1.5 cm in mature plant height.

Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line.
problem_activity: Activity
In this activity, students create two-way tables displaying relative frequency. The relative frequency table converts the actual frequency data to percentages which can be useful when comparing groups that include different totals. Finally, students use the relative frequencies to look for a pattern in the data. In the following lesson, students will work with associations in categorical data more explicitly. In this activity, students should use an informal understanding of association to think about whether one is present in the data based on the relative frequency table.
Launch
Keep students in groups of 2–3. After an introduction to relative frequency tables, allow students 3 minutes quiet work time followed by partner discussion and whole-class discussion.
Display the table for all to see.
{"table": [{"_attributes": {"border": "1"}, "thead": [{"tr": [{"th": [{"_attributes": {"scope": "col"}}, {"_attributes": {"scope": "col"}, "_value": "watch the news daily"}, {"_attributes": {"scope": "col"}, "_value": "does not watch the news daily"}, {"_attributes": {"scope": "col"}, "_value": "total"}]}]}], "tbody": [{"tr": [{"th": [{"_value": "younger than 18"}], "td": [{"_value": "30"}, {"_value": "80"}, {"_value": "110"}]}, {"th": [{"_value": "18 or older"}], "td": [{"_value": "10"}, {"_value": "5"}, {"_value": "15"}]}, {"th": [{"_value": "total"}], "td": [{"_value": "40"}, {"_value": "85"}, {"_value": "125"}]}]}]}]}
Ask students, "Based on this data, who is more likely to watch the news daily: someone who is younger than 18 or someone who is 18 or older?"
Tell students that, based on the numbers in the table, there are more younger people who watch the news (30) than older (10). On the other hand, the survey reached out to 110 young people and only 15 older people. Without looking at the whole table, that information may have been missed.
In cases like this, finding a relative frequency including percentages can be more helpful than looking at the actual frequency, which is what they are going to do now.
Use MLR 2 (Collect and Display) to co-create a graphic organizer with students comparing and contrasting the definitions and characteristics of “actual frequency” and “relative frequency” to be referenced and revised throughout this and later activities.
Conversing, Representing, Writing: MLR2 Collect and Display.
As students work in groups, capture the vocabulary and phrases students use when comparing and contrasting the definitions and characteristics of “actual frequency” and “relative frequency.” Listen for students who identify pros and cons for each representation and when one is preferable compared to the other. Record their language on a visual display that can be referenced in future discussions. This routine provides feedback to students that supports sense-making and increases meta-awareness of mathematical language.
Design Principle(s): Support sense-making; Maximize meta-awareness
Student Facing
Here is a two-way table that shows data about cell phone usage among children aged 10 to 18.
{"table": [{"_attributes": {"border": "1"}, "thead": [{"tr": [{"th": [{"_attributes": {"scope": "col"}}, {"_attributes": {"scope": "col"}, "_value": "has cell phone"}, {"_attributes": {"scope": "col"}, "_value": "does not have cell phone"}, {"_attributes": {"scope": "col"}, "_value": "total"}]}]}], "tbody": [{"tr": [{"th": [{"_value": "10 to 12 years old"}], "td": [{"_value": "25"}, {"_value": "35"}, {"_value": "60"}]}, {"th": [{"_value": "13 to 15 years old"}], "td": [{"_value": "40"}, {"_value": "10"}, {"_value": "50"}]}, {"th": [{"_value": "16 to 18 years old"}], "td": [{"_value": "50"}, {"_value": "10"}, {"_value": "60"}]}, {"th": [{"_value": "total"}], "td": [{"_value": "115"}, {"_value": "55"}, {"_value": "170"}]}]}]}]}
Complete the table. In each row, the entries for “has cell phone” and “does not have cell phone” should have the total 100%. Round entries to the nearest percentage point.
{"table": [{"_attributes": {"border": "1"}, "thead": [{"tr": [{"th": [{"_attributes": {"scope": "col"}}, {"_attributes": {"scope": "col"}, "_value": "has cell phone"}, {"_attributes": {"scope": "col"}, "_value": "does not have cell phone"}, {"_attributes": {"scope": "col"}, "_value": "total"}]}]}], "tbody": [{"tr": [{"th": [{"_value": "10 to 12 years old"}], "td": [{"_value": "42%"}, {}, {}]}, {"th": [{"_value": "13 to 15 years old"}], "td": [{}, {}, {"_value": "100%"}]}, {"th": [{"_value": "16 to 18 years old"}], "td": [{}, {"_value": "17%"}, {}]}]}]}]}
This is still a two-way table. Instead of showing
frequency
, this table shows
relative frequency
.
Two-way tables that show relative frequencies often don’t include a “total” row at the bottom. Why?
Is there an association between age and cell phone use? How does the two-way table of relative frequencies help to illustrate this?
Student Response
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Student Facing
Are you ready for more?
A pollster attends a rally and surveys many of the participants about whether they associate with political Party A or political Party B and whether they are for or against Proposition 3.14 going up for vote soon. The results are sorted into the table shown.
{"table": [{"_attributes": {"border": "1"}, "thead": [{"tr": [{"th": [{"_attributes": {"scope": "col"}}, {"_attributes": {"scope": "col"}, "_value": "for"}, {"_attributes": {"scope": "col"}, "_value": "against"}]}]}], "tbody": [{"tr": [{"th": [{"_value": "party A"}], "td": [{"_value": "832"}, {"_value": "165"}]}, {"th": [{"_value": "party B"}], "td": [{"_value": "80"}, {"_value": "160"}]}]}]}]}
A news station reports these results by saying, “A poll shows that about the same number of people from both parties are voting against Proposition 3.14.”
A second news station shows this graphic.
[IMG]
Are any of the news reports misleading? Explain your reasoning.
Create a headline, graphic, and short description that more accurately represents the data in the table.
Student Response
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for free access to Extension Student Response.
Anticipated Misconceptions
Students may not calculate relative frequencies correctly. Look to see if they are dividing into the total for each row, instead of some other number in the row, or the total for the entire table.
Activity Synthesis
The purpose of this discussion is to help students see the usefulness of two-way tables that display relative frequency.
Some questions for discussion:
“What does the 42% in table mean?” (42% of people 10 to 12 years old have a cell phone.)
“What is the total of the percentages in the first column? What's wrong with that answer?” (205%. It doesn't make sense since it is greater than 100%. It is combining percentages of different wholes, so it doesn't make sense to add them.)
“Did you say there was or was not an association between age and cell-phone use? Explain your reasoning.” (There is an association since the percentages for the 10 to 12 year olds is very different from the other two age groups.)
“What did the relative frequency table show you that was harder to see in the original two-way table?” (It was much easier to see the association with the percentages than the numbers. For example, the number of people without a cell phone for the older 2 age groups was the same, but the percentages were a little different.)


correct_option_index: 0