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Flashback 8-22-12 Use the table that shows the number of goals Pierre scored playing hockey to answer problems 1–3. 1. Using the data from 2001 and 1997,

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Presentation on theme: "Flashback 8-22-12 Use the table that shows the number of goals Pierre scored playing hockey to answer problems 1–3. 1. Using the data from 2001 and 1997,"— Presentation transcript:

1 Flashback Use the table that shows the number of goals Pierre scored playing hockey to answer problems 1–3. 1. Using the data from 2001 and 1997, find the slope of the line. 2. With your answer from problem 1 and the point (2000, 19), write an equation for the line in slope-intercept form. 3. Using your answer from problem 2, how many goals should Pierre score in 2004? Year Goals 1997 26 1998 24 1999 20 2000 19 2001 15

2 If there are 4 apples and you take away 3, how many do you have?
Joke of the day If there are 4 apples and you take away 3, how many do you have?

3 You took 3 apples so obviously you have 3.

4 Steps Enter data into calculator. (STAT, edit, L1, L2)
Turn stat plot on. (2nd, y=, on, enter) Change window (window, x and y values will need to be changed) Calculate linear regression. (STAT, CALC, 4) Enter equation into calculator (y=) Graph. Compare line to stat plot.

5 Graphically Algebraically Y= 79.957x-153848.716
We are looking for a prediction of population in 2010, so substitute for x. or about 6865 Graphically Find value at

6 Interpret The population in 2010 should be about 6865 million people according to the regression.

7 Now, it’s your turn… Complete the worksheet with a partner.
Be prepared to present your solutions with the class.

8 Exit Slip Complete problem 45 on p. 10

9 Flashback Write an equation for the line that satisfies the given conditions. 1) through: (1, 2), slope = 7 2) through: (4, 2), parallel to y =-3/4 x- 5 3) through: (2, 5), slope = undefined

10 Joke of the day There are three types of people in the world, those who can count and those who can't.

11

12 Regression Analysis The process of finding a curve that most closely fits a set of data. The curve is called the regression curve. A line is considered a curve in this situation.

13 Steps for Regression analysis
Plot the data on a scatter plot. Find the regression equation. (Line of best fit in this situation.) Graph the regression equation on the scatter plot to see the fit. Use the regression equation to predict values not given by data.

14 Example Year Population (millions) 1980 4454 1985 4853 1990 5285 1995
5696 2003 6305 2004 6378 2005 6450

15 Steps Enter data into calculator. (STAT, edit, L1, L2)
Turn stat plot on. (2nd, y=, on, enter) Change window (window, x and y values will need to be changed) Calculate linear regression. (STAT, CALC, 4) Enter equation into calculator (y=) Graph. Compare line to stat plot.

16 Graphically Algebraically Y= 79.957x-153848.716
We are looking for a prediction of population in 2010, so substitute for x. or about 6865 Graphically Find value at

17 Interpret The population in 2010 should be about 6865 million people according to the regression.

18 Now, it’s your turn… Complete the worksheet with a partner.
Be prepared to present your solutions with the class.

19 Exit Slip Use the table that shows the number of goals Pierre scored playing hockey to answer problems 1–3. 1. Using the data from 2001 and 1997, find the slope of the line. 2. With your answer from problem 1 and the point (2000, 19), write an equation for the line in slope-intercept form. 3. Using your answer from problem 2, how many goals should Pierre score in 2004? Year Goals 1997 26 1998 24 1999 20 2000 19 2001 15

20 Joke of the day There are three types of people in the world, those who can count and those who can't.

21

22 Regression Analysis The process of finding a curve that most closely fits a set of data. The curve is called the regression curve. A line is considered a curve in this situation.

23 Steps for Regression analysis
Plot the data on a scatter plot. Find the regression equation. (Line of best fit in this situation.) Graph the regression equation on the scatter plot to see the fit. Use the regression equation to predict values not given by data.

24 Example Year Population (millions) 1980 4454 1985 4853 1990 5285 1995
5696 2003 6305 2004 6378 2005 6450

25 Steps Enter data into calculator. (STAT, edit, L1, L2)
Turn stat plot on. (2nd, y=, on, enter) Change window (window, x and y values will need to be changed) Calculate linear regression. (STAT, CALC, 4) Enter equation into calculator (y=) Graph. Compare line to stat plot.

26 Graphically Algebraically Y= 79.957x-153848.716
We are looking for a prediction of population in 2010, so substitute for x. or about 6865 Graphically Find value at

27 Interpret The population in 2010 should be about 6865 million people according to the regression.

28 Now, it’s your turn… Complete the worksheet with a partner.
Be prepared to present your solutions with the class.

29 Exit Slip


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