1. Splash Screen

2. Lesson Menu Five-Minute Check (over Lesson 2–4) CCSS Then/Now New Vocabulary Key Concept: Scatter Plots Example 1:Real-World Example: Use a Scatter Plot and Prediction Equation Example 2:Real-World Example: Regression Line

3. Over Lesson 2–4 5-Minute Check 1 A. B. C. D. Write an equation in slope-intercept form for the line with slope =, passing through (0, 1).

4. Over Lesson 2–4 5-Minute Check 2 A. B. C. D. Write an equation in slope-intercept form for the line with slope = –1, passing through

5. Over Lesson 2–4 5-Minute Check 3 What is the slope-intercept form of 4x + 8y = 11? A.4x + 8y – 11 = 0 B.y = 4x – 11 C. D.

6. Over Lesson 2–4 5-Minute Check 4 A.6x – y = 7 B.y = –6x + 7 C.x – 7y = 1 D.y = x + 7 Write an equation in slope-intercept form of a line that passes through (1, 1) and (0, 7).

7. Over Lesson 2–4 5-Minute Check 5 A.y = 35x + 65 B.65 = 35x + y C.y = 65x + 35 D.total = 35x + 65y A plumber charges a flat fee of $65, and an additional $35 per hour for a service call. Write an equation that represents the charge y for a service call that lasts x hours.

8. Over Lesson 2–4 5-Minute Check 6 What is the equation of a line that passes through the point (6, –4) and is perpendicular to the line with the equation A.e B.e C.e D.e

9. CCSS Content Standards F.IF.4 For a function that models a relationship between two quantities, interpret key features of graphs and tables in terms of the quantities, and sketch graphs showing key features given a verbal description of the relationship. Mathematical Practices 4 Model with mathematics. 5 Use appropriate tools strategically.

10. Then/Now You wrote linear equations. Use scatter plots and prediction equations. Model data using lines of regression.

11. Vocabulary bivariate dataregression line correlation coefficient scatter plot dot plot positive correlation negative correlation line of fit prediction equation

12. Concept

13. Example 1A Use a Scatter Plot and Prediction Equation A. EDUCATION The table below shows the approximate percent of students who sent applications to two colleges in various years since 1985. Make a scatter plot of the data and draw a line of fit. Describe the correlation.

14. Example 1A Use a Scatter Plot and Prediction Equation Graph the data as ordered pairs, with the number of years since 1985 on the horizontal axis and the percentage on the vertical axis. Answer: The data show a strong negative correlation. The points (3, 18) and (15, 13) appear to represent the data well. Draw a line through these two points.

15. Example 1B Use a Scatter Plot and Prediction Equation B. Use two ordered pairs to write a prediction equation. Find an equation of the line through (3, 18) and (15, 13). Begin by finding the slope. Slope formula Substitute. Simplify.

16. Example 1B Use a Scatter Plot and Prediction Equation Point-slope form Substitute. Distributive Property Simplify.Answer: One prediction equation is

17. Example 1C Use a Scatter Plot and Prediction Equation C. Predict the percent of students who will send applications to two colleges in 2010. The year 2010 is 25 years after 1985, so use the prediction equation to find the value of y when x = 25. Answer: The model predicts that the percent in 2010 should be about 8.83%. x = 25 Prediction equation Simplify.

18. Example 1D Use a Scatter Plot and Prediction Equation D. How accurate is this prediction? Answer: Except for the point at (6, 15), the line fits the data well, so the prediction value should be fairly accurate.

19. Example 1A A. SAFETY The table shows the approximate percent of drivers who wear seat belts in various years since 1994. Which shows the best line of fit for the data?

20. Example 1A A.B. C.D.

21. Example 1B B. The scatter plot shows the approximate percent of drivers who wear seat belts in various years since 1994. What is a good prediction equation for this data? Use the points (6, 71) and (12, 81). A. B. C. D.

22. Example 1C A.83% B.87% C.90% D.95% C. The equation represents the approximate percent of drivers y who wear seat belts in various years x since 1994. Predict the percent of drivers who will be wearing seat belts in 2010.

23. Example 1D D. How accurate is the prediction about the percent of drivers who will wear seat belts in 2010? A.There are no outliers so it fits very well. B.Except for the one outlier the line fits the data very well. C.There are so many outliers that the equation does not fit very well. D.There is no way to tell.

24. End of the Lesson

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