4.7 Predict with Linear Models
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Warm-Up Exercises 4.7 Predict with Linear Models • You will make predictions using best- fitting lines. • Essential Question: How can you use a best-fitting line to make predictions about data? Predict! You they will learn how to answer this question by performing a linear regression.
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4.7 Predict with Linear Models. Predict!. You will make predictions using best-fitting lines. Essential Question: How can you use a best-fitting line to make predictions about data?. You they will learn how to answer this question by performing a linear regression. EXAMPLE 1. - PowerPoint PPT Presentation
Transcript of 4.7 Predict with Linear Models
4.7 Predict with Linear Models
• You will make predictions using best-fitting lines.
• Essential Question: How can you use a best-fitting line to make predictions about data?
Predict!
You they will learn howto answer this question by performing a linear regression.
Warm-Up ExercisesInterpolate using an equationEXAMPLE 1
CD SINGLES
The table shows the total number of CD single shipped (in millions) by manufacturers for several years during the period 1993–1997.
Warm-Up ExercisesInterpolate using an equationEXAMPLE 1
Make a scatter plot of the data.
b. Find an equation that models the number of CD singles shipped (in millions) as a function of the number of years since 1993.
c. Approximate the number of CD singles shipped in 1994.
a.
Warm-Up ExercisesInterpolate using an equationEXAMPLE 1
SOLUTION
a. Enter the data into lists on a graphing calculator. Make a scatter plot, letting the number of years since 1993 be the x-values (0, 2, 3, 4) and the number of CD singles shipped be the y-values.
b. Perform linear regression using the paired data. The equation of the best-fitting line is approximately y = 14x + 2.4.
Warm-Up ExercisesInterpolate using an equationEXAMPLE 1
c. Graph the best-fitting line. Use the trace feature and the arrow keys to find the value of the equation when x = 1.
ANSWER
About 16 million CD singles were shipped in 1994.
Warm-Up ExercisesExtrapolate using an equationEXAMPLE 2
CD SINGLES
Look back at Example 1.
a. Use the equation from Example 1 to approximate the number of CD singles shipped in 1998 and in 2000.
b. In 1998 there were actually 56 million CD singles shipped. In 2000 there were actually 34 million CD singles shipped. Describe the accuracy of the extrapolations made in part (a).
Warm-Up ExercisesExtrapolate using an equationEXAMPLE 2
SOLUTION
a. Evaluate the equation of the best-fitting line from Example 1 for x = 5 and x = 7. The model predicts about 72 million CD singles shipped in 1998 and about 100 million CD singles shipped in 2000.
Warm-Up ExercisesExtrapolate using an equationEXAMPLE 2
b. The differences between the predicted number of CD singles shipped and the actual number of CD singles shipped in 1998 and 2000 are 16 million CDs and 66 million CDs, respectively. The difference in the actual and predicted numbers increased from 1998 to 2000. So, the equation of the best-fitting line gives a less accurate prediction for the year that is farther from the given years.
Warm-Up ExercisesGUIDED PRACTICE for Examples 1 and 2
1. HOUSE SIZE The table shows the median floor area of new single-family houses in the United States during the period 1995–1999.
a. Find an equation that models the floor area (in square feet) of a new single-family house as a function of the number of years since 1995.
ANSWER y = 26.6x + 1921.4
Warm-Up ExercisesGUIDED PRACTICE for Examples 1 and 2
c. Which of the predictions from part (b) would you expect to be more accurate? Explain your reasoning.
b. Predict the median floor area of a new single-family house in 2000 and in 2001.
ANSWER about 2054.4 ft2, about 2081 ft2
ANSWERThe prediction for 2000 because the farther removed an x-value is from the known x-values, the less confidence you can have in the accuracy of the predicted y-value.
Warm-Up Exercises
SOFTBALL
EXAMPLE 3 Predict using an equation
The table shows the number of participants in U.S. youth softball during the period 1997–2001. Predict the year in which the number of youth softball participants reaches 1.2 million.
Year 1997 1998 1999 2000 2001Participants (millions) 1.44 1.4 1.411 1.37 1.355
Warm-Up Exercises
SOLUTION
EXAMPLE 3 Predict using an equation
Perform linear regression. Let x represent the number of years since 1997, and let y represent the number of youth softball participants (in millions). The equation for the best-fitting line is approximately y = –0.02x + 1.435.
STEP 1
Warm-Up ExercisesEXAMPLE 3 Predict using an equation
STEP 2Graph the equation of the best-fitting line. Trace the line until the cursor reaches y = 1.2. The corresponding x-value is shown at the bottom of the calculator screen.
ANSWERThere will be 1.2 million participants about 12 years after 1997, or in 2009.
Warm-Up ExercisesGUIDED PRACTICE for Example 3
2. SOFTBALL In Example 3, in what year will there be 1.25 million youth softball participants in the U.S?
ANSWER
2006
Warm-Up Exercises
SOLUTION
SOFTBALL
EXAMPLE 4 Find the zero of a function
Look back at Example 3. Find the zero of the function. Explain what the zero means in this situation.
Substitute 0 for y in the equation of the best-fitting lineand solve for x.
y = –0.02x + 1.435 Write the equation.
0 = –0.02x + 1.435 Substitute 0 for y.
x 72 Solve for x.
Warm-Up ExercisesEXAMPLE 4 Find the zero of a function
ANSWERThe zero of the function is about 72. The function has a negative slope, which means that the number of youth softball participants is decreasing. According to the model, there will be no youth softball participants 72 years after 1997, or in 2069.
Warm-Up ExercisesGUIDED PRACTICE for Example 4
JET BOATS The number y (in thousands) of jet boats purchased in the U.S. can be modeled by the function y = –1.23x + 14 where x is the number of years since 1995. Find the zero of the function. Explain what the zero means in this situation.
3.
ANSWER11.4; the function has a negative slope, which means that the number of jet boats purchased in the U.S. is decreasing. According to the model, there will be no jet boats purchased 11.4 years after 1995, or in 2006.
• You will make predictions using best-fitting lines.
• Essential Question: How can you use a best-fitting line to make predictions about data?• You can
approximate anunknown data value by using theequation of the best-fitting linefound by linear regression.• The zero of a function is the xvalue of the point where the linecrosses the x-axis.
Make a scatter plot of the data and then perform a linear regression to find the equation of the best-fitting line. Use the trace feature of the graphing calculator to trace the line of the equation or evaluate the equation of the best-fitting line to find the predicted values. Substitute 0 for y in the equation to find the zero of the function.
Warm-Up ExercisesDaily Homework Quiz
1. Find the zero of the function f(x) = 2.5x – 6.
ANSWER 2.4
Warm-Up ExercisesDaily Homework Quiz
ANSWER
y = –0.2x + 2.35, where x is the number of years after 1998. The model predicts about 2150 video rentals in 1999 and 1350 video rentals in 2003.
2. The table shows the number of video rentals at a store from 1998 to 2002. Find an equation that models the number of video rentals as a function of the number of years since 1998. Predict the number of rentals in 1999 and 2003.
