Analysis of Smokers

ANALYSIS OF SMOKERS IN THE UNITED STATES

Enduring Understanding: Develop a better understanding of how to use data from a table to create a graph and make a prediction of values not included in the data set.

Essential Questions:

Original Lesson Design / Suggestions for English Language Learners
· What is an informative/meaningful title for a graph?
· What are appropriate intervals for the x- and y-axes?
· How is a line that fits data displayed on a scatter plot (fitted line) determined?
· How is a fitted line represented as an equation?
· How is a fitted line used to make a prediction?
· When reading a graph, where are the x- and y-intercepts? What is the relationship between the intercepts and the context of any problem?
· What does it mean to have negative values when you are working with years?
· How do you make predictions to non-linear sets of data? / Enhance Vocabulary:
Prediction
Evidence
Intervals
x-axis, y-axis
Fitted line
Negative
Non-linear
Scatterplot
x-intercept, y-intercept
Equation

Lesson Overview:

Original Lesson Design / Suggestions for English Language Learners
· Before allowing the students the opportunity to start the activity: access their prior knowledge with regards to smoking among their peers and adults they know. Discuss the recent smoking ban in the state. How has that affected them and their families? Is the ban a good or bad thing? Is the smoking ban an economic plus or minus for businesses? Discuss health issues as they relate to smoking. Is smoking allowed on their campus?
· Add in a matching section on the overhead or on paper with several graphs or data tables or equations and the students match them up.
· Discuss a “fitted line”—What is it? How would a person use a fitted line? How would you show an understanding of a fitted line? Why do you think a fitted line is used? What would happen if a person inaccurately used a fitted line? What operations are necessary to create a fitted line?
· How are the intervals on a graph determined?
· How can you support a conclusion that you make? What evidence from graphs can be used to support/justify your conclusion?
· Use resources from your building. / · If available, use a motion sensor and graphing calculator with students and have them experiment with trying to match a graph provided by the calculator by walking across their classroom.
· Model at least one example of selecting a fitted line from a scatterplot.
· Discuss the necessary conditions for a scatterplot: scale, title, labels, accurate data
· Allow students to work in small groups to provide and justify a solution. Have several students present their solution and justification to the class.

EALRs/GLEs

1.4.4

1.4.5

1.4.6

1.5.2

1.5.4

3.1.1

4.2.2

5.1.1

Item Specifications: PS03; AS02; SR03; CU02; MC01

Assessment:

· Use WASL format items that link to what is being covered by the classroom activity

· Include multiple choice questions

Analysis of Smokers in the United States

The Percentage of Adult* Daily Smokers in the United States 1974-2001

Year
(x) / 1974
(1) / 1979
(6) / 1985
(12) / 1992
( ) / 1997
( ) / 1999
( ) / 2001
( )

Percent

of Adult
smokers
(y) / 37.2 / 33.5 / 30 / 24.6 / 21.0 / 18.9 / 18.7

*Adult is defined as individuals 19 years of age and older and post high school

1. Complete the table for x and graph the data. Include negative values for x on your graph.

2. Draw a line (fitted line) that fits the data displayed on your scatter plot.

3. What is the y-intercept for your graph? ______

4. In real world terms, as they pertain to this data, what does the y-intercept mean?

______

5. Write an equation that describes the fitted line ______

6. In real world terms, as they pertain to this data, what does the x-intercept mean?

______

7. How likely is the x-intercept to become a reality? Explain your thinking.

______

8. What is the percentage of smokers likely to be in 2010? ______

9. Why did you choose the percentage that you wrote for question #9? ______

______

10. What other method could you have used to answer #10? ______

______

11. What does your model indicate for the percentage of smokers in 1953? ______

12. What does your model indicate for the percentage of smokers in 1923? ______

Cigarette Smoking Among Those Under 19 in the United States

The Percentage of Teenage Daily Smokers in the United States 1992-2001

1992
(1) / 1993
(2) / 1994
( ) / 1997
( ) / 1999
( ) / 2001
( )
8th graders / 7.0% / 8.3% / 8.8% / 9.0% / 8.1% / 5.5%
10th graders / 12.3% / 14.2% / 14.6% / 18.0% / 15.9% / 12.2%
12th graders / 17.2% / 19.0% / 19.4% / 24.6% / 23.1% / 19.0%

13. On the same graph, using different colors to represent the age groups, create a scatter plot of the data in the table. Complete the table for the values of x.

14. Would a straight line be appropriate for this data? Why or why not? ______

______

15. Describe the trend of the data and provide an explanation of why it may have occurred.

______

16. Make a prediction for all three grade-levels.

8th Grade ______

10th Grade ______

12th Grade ______

17. Predict the percentage of smokers in 1996 for all three grade-levels.

8th Grade ______

10th Grade ______

12th Grade ______

18. How likely is the x-intercept to become a reality? Explain your thinking.

______

19. The graph shows the thickness of the ice on a lake during the colder months.

Which of the following is closest to the number of days the ice was at least 3 inches thick?

A. 30

B. 45

C. 60

D. 75

20. The scatterplot below shows the ages and heights of 20 trees on a tree farm.

Let x = age in years and y = height in meters.

Which equation describes a line that fits the data displayed on this scatterplot?