250 200 150 100 50 0 Graph of Actual Bills (X axis) vs. Judgments (Y axis)...

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250 200 150 100 50 0 Graph of Actual Bills (X axis) vs. Judgments (Y axis) 50 100 150 200 250 Estimate of Achievement Index (Correlation Between Judgments and Actual Bills)= 3. Using Excel, compute the values for the table below. Lens Model Table: Utility Bill Estimation Task Number of bills correctly predicted= Sum of absolute differences between outcome and judgment= Outcome Mean= 95.44 Judgment Mean= Outcome Standard Deviation= 44.05 Judgment Standard Deviation= Achievement Index (correlation between judgments and actual bills)= Linear Achievement Index (Cue Validity X Cue Utilization Coefficient) = Nonlinear Achievement Index (Achievement Index - Linear Achievement Index)= Cue Validity = .83 Cue Utilization (correlation between Judgment and Temperature) = 4. a) Using the cue utilization coefficient and achievement indices that you computed using Excel, evaluate the accuracy of your scatter plot estimates of cue utilization coefficient and achievement index. Cue Utilization Coefficient Estimated from scatter plot = Achievement Index Estimated from scatter plot) = Computed using Excel = b) If they were inaccurate, how did you misjudge the scatter plot(s)? Cue Utilization Coefficient Achievement Index Computed using Excel = 021 001 02 5. a) Report the values and assess your accuracy on each of the following four dimensions: i) sum of absolute differences ii) achievement index iii) mean iv) standard deviation b) If the nonlinear achievement index is greater than .1, is it due to luck, cheating, using a cue not included in the analysis, and/or to using the cue in a nonlinear fashion (which matches the cue's relationship to the outcome)? c) For any problem dimension (sum of absolute differences, achievement index, mean, and standard deviation), identify a corresponding way to improve your accuracy. i) sum of absolute differences ii) achievement index iii) mean iv) standard deviation d) Compute and report the autocorrelation for actual electric bill? Lens Model: Interpreting a Lens Model Table with One Cue Sum of absolute differences between outcome and judgment= divide by number of judgments and interpret (then use common sense). Outcome and Judgment Means---Compare judgment mean to outcome mean. If it is too low, increase average judgment. If too high, reduce average judgment. Outcome and Judgment Standard Deviations---Compare to outcome standard deviation. If too low, increase spread. If too high, reduce spread. Achievement Index---interpret sign (direction) and absolute value (strength). Linear Achievement Index --- compare to cue validity (which in this simple case is equal to linear outcome predictability). If linear achievement index is lower, it can be increased to the cue validity through improved consistency and improved linear cue usage. (In this simple case, linear achievement index is equal to the product of cue validity and cue utilization coefficient.) Nonlinear Achievement Index ---If over .10, determine whether it is due to luck, cheating, use of an external cue, and/or using the cue in a nonlinear fashion which matches how it relates to the outcome. If less than or equal to .10, do not interpret. Linear Outcome Predictability (How good are the cues?)---Because there is only one cue, this is equal to the cue validity. If low, improve by adding new, useful cues. Linear Judgmental Predictability (How consistent was the judge?)--- Because there is only one cue, this is equal to the cue utilization coefficient. If low, improve through greater consistency in using the cue. Knowledge Linear (How well did the judge use the cues?)--In this simple case of one cue, knowledge linear match is always equal to one. Nonlinear ---Ignore. Cue Validities and Cue Utilization Coefficients---match cue usage to cue validities in terms of both sign and magnitude. 1.Enter your judgments and complete the table below: Average High Actual Month January February Temperature Electric Bill Your Judgment 63 $74 $80 66 $ 63 $69 March April May 73 $57 80 $ 68 86 $ 88 $50 $85 $90.0 June 91 $113 $100 July 94 alloede on $168 $118 August 95 $186 $1457 September 90 The $126 $120 October 82 $81 $82 November 73 $67 $62 December 64 $ 54 $ 50 2. Complete the graphs below and estimate cue utilization coefficient and achivement index from the graphs. Graph of Judgments (Y axis) vs. Temperature Cue (X axis) 250 200 150 100 Judy 50 SAD BUD 0 0 10 20 30 40 50 60 70 80 90 100 TEMP Estimate of Cue Utilization Coefficient (Correlation between Judgments and Temperature Cue)= 250 200 150 100 50 0 Graph of Actual Bills (X axis) vs. Judgments (Y axis) 50 100 150 200 250 Estimate of Achievement Index (Correlation Between Judgments and Actual Bills)= 3. Using Excel, compute the values for the table below. Lens Model Table: Utility Bill Estimation Task Number of bills correctly predicted= Sum of absolute differences between outcome and judgment= Outcome Mean= 95.44 Judgment Mean= Outcome Standard Deviation= 44.05 Judgment Standard Deviation= Achievement Index (correlation between judgments and actual bills)= Linear Achievement Index (Cue Validity X Cue Utilization Coefficient) = Nonlinear Achievement Index (Achievement Index - Linear Achievement Index)= Cue Validity = .83 Cue Utilization (correlation between Judgment and Temperature) = 4. a) Using the cue utilization coefficient and achievement indices that you computed using Excel, evaluate the accuracy of your scatter plot estimates of cue utilization coefficient and achievement index. Cue Utilization Coefficient Estimated from scatter plot = Achievement Index Estimated from scatter plot) = Computed using Excel = b) If they were inaccurate, how did you misjudge the scatter plot(s)? Cue Utilization Coefficient Achievement Index Computed using Excel = 021 001 02 5. a) Report the values and assess your accuracy on each of the following four dimensions: i) sum of absolute differences ii) achievement index iii) mean iv) standard deviation b) If the nonlinear achievement index is greater than .1, is it due to luck, cheating, using a cue not included in the analysis, and/or to using the cue in a nonlinear fashion (which matches the cue's relationship to the outcome)? c) For any problem dimension (sum of absolute differences, achievement index, mean, and standard deviation), identify a corresponding way to improve your accuracy. i) sum of absolute differences ii) achievement index iii) mean iv) standard deviation d) Compute and report the autocorrelation for actual electric bill? Lens Model: Interpreting a Lens Model Table with One Cue Sum of absolute differences between outcome and judgment= divide by number of judgments and interpret (then use common sense). Outcome and Judgment Means---Compare judgment mean to outcome mean. If it is too low, increase average judgment. If too high, reduce average judgment. Outcome and Judgment Standard Deviations---Compare to outcome standard deviation. If too low, increase spread. If too high, reduce spread. Achievement Index---interpret sign (direction) and absolute value (strength). Linear Achievement Index --- compare to cue validity (which in this simple case is equal to linear outcome predictability). If linear achievement index is lower, it can be increased to the cue validity through improved consistency and improved linear cue usage. (In this simple case, linear achievement index is equal to the product of cue validity and cue utilization coefficient.) Nonlinear Achievement Index ---If over .10, determine whether it is due to luck, cheating, use of an external cue, and/or using the cue in a nonlinear fashion which matches how it relates to the outcome. If less than or equal to .10, do not interpret. Linear Outcome Predictability (How good are the cues?)---Because there is only one cue, this is equal to the cue validity. If low, improve by adding new, useful cues. Linear Judgmental Predictability (How consistent was the judge?)--- Because there is only one cue, this is equal to the cue utilization coefficient. If low, improve through greater consistency in using the cue. Knowledge Linear (How well did the judge use the cues?)--In this simple case of one cue, knowledge linear match is always equal to one. Nonlinear ---Ignore. Cue Validities and Cue Utilization Coefficients---match cue usage to cue validities in terms of both sign and magnitude. 1.Enter your judgments and complete the table below: Average High Actual Month January February Temperature Electric Bill Your Judgment 63 $74 $80 66 $ 63 $69 March April May 73 $57 80 $ 68 86 $ 88 $50 $85 $90.0 June 91 $113 $100 July 94 alloede on $168 $118 August 95 $186 $1457 September 90 The $126 $120 October 82 $81 $82 November 73 $67 $62 December 64 $ 54 $ 50 2. Complete the graphs below and estimate cue utilization coefficient and achivement index from the graphs. Graph of Judgments (Y axis) vs. Temperature Cue (X axis) 250 200 150 100 Judy 50 SAD BUD 0 0 10 20 30 40 50 60 70 80 90 100 TEMP Estimate of Cue Utilization Coefficient (Correlation between Judgments and Temperature Cue)=