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DAILY GRADE #6 --- 20 minutes Test Ch 1 & 2 Mon THQ#2 Due Thurs

DAILY GRADE #6 --- 20 minutes Test Ch 1 & 2 Mon THQ#2 Due Thurs. AP STAT Section 3.2: Least Squares Regression Part 3: Interpreting Residual Plots. EQ: How do you use Residual Plots to assess how well a LSRL fits a data set?.

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DAILY GRADE #6 --- 20 minutes Test Ch 1 & 2 Mon THQ#2 Due Thurs

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  1. DAILY GRADE #6 --- 20 minutes • Test Ch 1 & 2 Mon • THQ#2 Due Thurs

  2. AP STAT Section 3.2: Least Squares Regression Part 3: Interpreting Residual Plots EQ: How do you use Residual Plots to assess how well a LSRL fits a data set?

  3. ---scatterplot of the regression residuals against the predicted value; assess how well a LSRL fits Residual Plots LINEAR ASSOCIATION: No Pattern Evident Pattern Evident NONLINEAR ASSOCIATION:

  4. Ex 1: No pattern in the residual plot, linear association appropriate

  5. Ex 2: No pattern in the residual plot, linear association appropriate

  6. Ex 3: Patternin the residual plot, linear association not appropriate.

  7. Ex 3: Patternin the residual plot, linear association not appropriate.

  8. Ex 3: Patternin the residual plot, linear association not appropriate.

  9. Ex 3: Patternin the residual plot, linear association not appropriate.

  10. Use your graphing calculator to create a residual plot using NEA and FAT. • To make sure the LAST regression equation your calculator found was for NEA vs FAT, recalculate the scatterplot and the LSRL forNEA vs FAT. • Now the residualsfor this plot are stored in a list called RESID.

  11. Use your graphing calculator to create a residual plot using NEA and FAT. • Go to STATPLOT and cut on PLOT1. Select the first graph. • Choose NEA as Xlist and RESID as Ylist.

  12. Use your graphing calculator to create a residual plot using NEA and FAT. • RESID is the list of the LAST RESIDUALS your calculator created. • ZOOM9 Compare to Residual Plot on p. 219.

  13. SCATTERPLOT LSRL RESIDUAL PLOT

  14. Go back to WS "Calculating Regression Lines“. Answer the question in Part 3. REMEMBER: You must recalculate the LSRL for this data because RESID contains the residuals from NEA and FAT.

  15. MUST HIT Points When Deciding Upon a Linear Association: [DON'T RELY ON JUST ONE] 1. Observe Scatterplot for Linearity 2. State Correlation Coefficient --- strong vs weak 3. State Coefficient of Determination --- strong vs weak 4. Observe Residual Plot --- pattern (nonlinear) vs no pattern (linear)

  16. Assignment : pp. 220 - 222 #39, 40, 42 pp. 227 - 228 #43, 44, 47, 48 pp. 230 - 233 #49 - 51, 53, 55

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