1.  To measure the time it takes to run the 100 yard dash  To measure the weight of a refrigerator  To measure the distance from C.S. to Denver  To measure the dining room table  Seconds  Pounds  Miles  Feet

2. Objective DOL  SWBAT represent data on a scatter plot and construct a line of best fit and make predictions. (3.1.b.ii)  Given 2 multiple choice problems and 1 constructed response problems (with 4 parts), students will represent data on a scatter plot, construct a line of best fit, and make predictions with 80% accuracy. Why? Used in business to make decisions about products to sell or discontinue.

3.  What do I need to study most about scatter plots and writing equations to be successful on the quiz tomorrow?

4.  Positive – as the independent variable increases, the dependent variable increases  Negative – as the independent variable increases, the dependent variable decreases  Sketch a positive and negative correlation in your notes:

5.  A - Positive  B - Negative  C - No Correlation

6.  A - Positive  B - Negative  C - No Correlation

7.  The size of the car and its fuel efficiency  Independent – size of car  Dependent – fuel efficiency  Correlation – Negative; as the size of the car gets bigger, the fuel efficiency becomes less.

8.  Your score on a test compared to hours spent studying  Independent – hours studying  Dependent – test score  Correlation – Positive; as the hours studying increase, the test scores go up.

9.  Time spent on treadmill and calories burned  Independent – time on treadmill  Dependent – calories burned  Correlation – Positive; The more time spent on the treadmill, the more calories that will be burned

10. City Elevati on (feet) Average Precipitat ion (inches) Stockholm, Sweden17121 Berlin, Germany19023 London, England20330 Paris, France*21326 Bucharest, Romania*29823 Budapest, Hungary456 20 Toronto, Canada56731  Using the table, write a prediction equation for a line of best fit going through Paris, France and Bucharest, Romania.  26 – 233  213 - 298-85  m = -.04  26 = -.04(213) + b  26 = -8.52 + b  34.52 = b  y =.04x + 34.52 First things first – identify the Independent and dependent variable

11.  y = -0.04x + 34.52  y = -.04(279) + 34.52  y = -11.16 + 34.52  y = 23.36  Now using your prediction equation, predict the average annual precipitation for Dublin, Ireland, which has an elevation of 279 feet.  1) 25 inches  2) 23 inches  3) 1844 inches  4) 203 inches

12. YearPeople (millons) 198029.3 198533.1 199033.6 199536.4 199834.5 2012??  Write a prediction equation using (1980, 29.3) and (1990, 33.6)  29.3 – 33.6 -4.3  1980-1990 -10  m =.43  29.3 =.43(1980) + b  29.3 = 851.4 + b  -822.1 = b  y = 0.43x – 822.1 First things first – identify the Independent and dependent variable

13. YearPeople (millons) 198029.3 198533.1 199033.6 199536.4 199834.5 2012??  y = 0.43x – 822.1  y = 0.43(2012) – 822.1  y = 865.16 – 822.1  y = 43.06  Approximately 43.06 people are predicted to be below the poverty level in 2012.

14. YearEarnings ($) 1985343 1990412 1995479 1999549 2012??  Write an equation using (1990, 412) and (1985, 343)  y = 13.8x – 27050  2012, 715.6 First things first – identify the Independent and dependent variable

15.  Work on the problem marked on your paper on your own.  Find the person with the same problem and color as you.  Compare your work on the first problem and make changes.  Complete the second problem together.

16.  (19, 126) and (26, 173)  126 – 173 -47  19 – 26-7  m = 6.7  126 = 6.7(19) + b  126 = 127.3 + b  -1.3 = b  y = 6.7x – 1.3

17.  (5.1, 56) and (9.0, 40)  56 – 40 16  5.1 – 9.0 -3.9  m = -4.1  40 = -4.1(9) + b  40 = -36.9 + b  76.9 = b  y = -4.1x + 76.9

18.  (17, 24) and (75, 52)  24 – 52 -28  17 – 75 -58  m =.48  24 =.48(17) + b  24 = 8.16 + b  15.84 = b  y =.48x + 15.84

19.  (9, 6.0) and (41, 1.2)  6.0 – 1.2 4.8  9 – 41 -32  m = -.15  6.0 = -.15(9) + b  6.0 = -1.35 + b  7.35 = b  y = -.15x + 7.35

20. YearsSales ($) 69000 56000 34000 13000 46000 35000 68000 22000  Create a scatter plot.  Draw a line of best fit.  Write a prediction equation.  Predict the sales for a representative with 8 years of experience. First things first – identify the Independent and dependent variable

21.  What do I need to study most about scatter plots and writing equations to be successful on the quiz tomorrow?

22.  Determine correlation

23. Year Homes w/ Internet (in millions) 199510.1 199850.6 200187.2 2004129.1 2007171.6 2010208.6 Create a scatter plot. Use the fourth and sixth set of points to write a prediction equation Draw a line of best fit How many homes will have internet in 2020? Make a prediction. Explain how you determined your prediction.

24.  Determine correlation B B

25. Year Homes w/ Internet (in millions) 199510.1 199850.6 200187.2 2004129.1 2007171.6 2010208.6  y = 13.25x – 26423.9

26.  Prediction: 341.1 million homes  Research will not be true  Grading scale:  1 – axes correctly labeled  1 – points plotted  2 – line of best fit  1 – slope of line  1 – y-intercept  1 – equation of line  1 – plugging in for correct variable  1 – correct prediction  1 – correct explantation