 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

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.

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

 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:

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

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

 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.

 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.

 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

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

 y = -0.04x  y = -.04(279)  y =  y =  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

YearPeople (millons) ??  Write a prediction equation using (1980, 29.3) and (1990, 33.6)  29.3 –   m =.43  29.3 =.43(1980) + b  29.3 = b  = b  y = 0.43x – First things first – identify the Independent and dependent variable

YearPeople (millons) ??  y = 0.43x –  y = 0.43(2012) –  y = –  y =  Approximately people are predicted to be below the poverty level in 2012.

YearEarnings ($) ??  Write an equation using (1990, 412) and (1985, 343)  y = 13.8x –  2012, First things first – identify the Independent and dependent variable

 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.

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

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

 (17, 24) and (75, 52)  24 –  17 –  m =.48  24 =.48(17) + b  24 = b  = b  y =.48x

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

YearsSales ($)  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

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

 Determine correlation

Year Homes w/ Internet (in millions) 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.

 Determine correlation B B

Year Homes w/ Internet (in millions)  y = 13.25x –

 Prediction: 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