The Line of Best Fit CHAPTER 2 LESSON 3  Observed Values- Data collected from sources such as experiments or surveys  Predicted (Expected) Values-

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Presentation transcript:

The Line of Best Fit CHAPTER 2 LESSON 3

 Observed Values- Data collected from sources such as experiments or surveys  Predicted (Expected) Values- Points predicted by the linear model  Errors (Deviation)- The differences between observed and predicted values of the dependent variable  Line of Best Fit- The line with the smallest value for the sum of the squares of the errors  Method of Least Squares- The process of finding the line of best fit  Interpolation- Estimating a value between known values of data  Extrapolation- Estimating a value beyond known values of data  Center of Gravity- The one point on the line of best fit that can be determined by hand without much trouble VOCABULARY

 On your calculator  Press the STAT button  Press ENTER on option 1:Edit  Fill out Tables L1 and L2  Press the STAT button  Go to the CALC tab  Option number 4: LinReg(ax+b)  Select Calculate  Press Enter CALCULATING THE LINE OF BEST FIT

 LinReg  Y=ax+b  A= some #  B= some #  Round to 3 decimal places READING LINEAR REGRESSION

 Press STAT  Select Option 1: Edit..  Highlight L1 on top  Hit clear, then enter  Highlight L2 on top  Hit clear, then enter CLEARING TABLES AFTER LINREG

 The center of gravity is the one point on the linear regression line that can be calculated by hand  To find the x coordinate of the center of gravity, find the mean of all the observed x values  To find the y coordinate of the center of gravity, find the mean of all the observed y values CENTER OF GRAVITY

 Observed value – Predicted value  Observed value comes from the table given to you  Predicted value comes from the regression equation FINDING ERROR IN DATA

EXAMPLE CwCn

CONTINUED Cw Observed CnPredicted CnErrorError 2

 Worksheet 2-3 HOMEWORK