1. College Prep Stats

4. x is the independent variable (predictor variable) ^ y = b 0 + b 1 x ^ y = mx + b b 0 = y - intercept b 1 = slope y is the dependent variable (response variable)

5. y -intercept of regression equation  0 b 0 Slope of regression equation  1 b 1 Equation of the regression line y =  0 +  1 x y = b 0 + b 1 Population Parameter Sample Statistic

6. 1. We are investigating only linear relationships. 2. For each x value, y is a random variable having a normal (bell-shaped) distribution. All of these y distributions have the same variance. Also, for a given value of x, the distribution of y- values has a mean that lies on the regression line. (Results are not seriously affected if departures from normal distributions and equal variances are not too extreme.)

7. b 0 = (y-intercept) (  y) (  x 2 ) - (  x) (  xy) n(  xy) - (  x) (  y) n(  x 2 ) - (  x) 2 b 1 = (slope) n(  x 2 ) - (  x) 2

8.  Enter Data values in L1 and L2  Go to STAT-CALC-LinReg (a+bx)

9. 0.27 2 1.41 3 2.19 3 2.83 6 2.19 4 1.81 2 0.85 1 3.05 5 Data from the Garbage Project x Plastic (lb) y Household Construct the regression line for the following data:

12.  Predict the tip on a bill of $75  Predict the size of a family that discards 0.5 pounds of plastic per week  Predict the IQ of a 7 foot tall male.

13.  P.549: 15-18