Business Experiments with R - B. D. McCullough

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rel="nofollow" href="#ulink_3b983800-d3e6-59ff-9752-974eb15add60">7.3 The Determinant of a Matrix 7.4 Aliasing 7.5 Blocking (Again) 7.6 Mee's Blunders 7.7 Chapter Exercises 7.8 Learning More 7.9 Appendix on aliasMatrix and colorMap

      16  8 Two‐Level Screening Designs 8.1 Preliminaries 8.2 Case: Puncture Resistance (Small Screening Experiment) 8.3 Case: College Giving (Big Screening Experiment) 8.4 How to Set Up a Screening Experiment 8.5 Creating a Screening Design 8.6 Chapter Exercises 8.7 Learning More

      17  9 Custom Design of Experiments 9.1 Case: Selling Used Cars at Auction I (Small Custom Screening) 9.2 Case: Selling Used Cars at Auction II (Custom Experiment) 9.3 Custom Experiment with Blocking 9.4 Custom Screening Experiments 9.5 More Than Two Levels 9.6 Chapter Exercises 9.7 Learning More

      18  10 Epilogue 10.1 The Sequential Nature of Experimentation 10.2 Approaches to Sequential Experimentation

      19  References

      20  Index

      21  End User License Agreement

      List of Tables

      1 Chapter 1Table 1.1 Credit default rates for men and women.Table 1.2 Credit default rates by marital status.Table 1.3 Results of first Salk vaccine field trial.Table 1.4 Results of second Salk vaccine field trial.Table 1.5 Factors and levels for financial services example.Table 1.6 Summary of web test results.

      2 Chapter 2Table 2.1 Data from sales calls test.Table 2.2 Summary statistics for audio and video sales calls.Table 2.3 Errors in hypothesis tests.Table 2.4 Data from email response test.Table 2.5 Confidence intervals for the difference in response rate between em...Table 2.6 Power for two‐sample comparison of proportions,

.Table 2.7 Summary statistics for sales.Table 2.8 Results of hotel display ad test.

      3 Chapter 4Table 4.1 Summary statistics on sales for subgroup data, zeros excluded..Table 4.2 Contingency table for aggregate A/B test.Table 4.3 Contingency table for subgroup “loan = yes” A/B test.Table 4.4 Contingency table for subgroup “amount

” A/B test.Table 4.5 Admission to Berkeley graduate school by sex.Table 4.6 Credit default rates for men and women.Table 4.7 Kidney stone success rates.Table 4.8 Simpson's paradox in batting averages.Table 4.9 Simpson's paradox in voting.Table 4.10 Simpson's paradox in editing.Table 4.11 Simpson's paradox: septic shock example.Table 4.12 One‐sided alternatives and intervals.

      4 Chapter 5Table 5.1 One‐way ANOVA on call center scripts.Table 5.2 Crosstab of counts for scripts A, B, C, and D and agents 1, 2, 3, 4...Table 5.3 One‐way ANOVA with blocking on call center data.Table 5.4 Tukey HSD intervals for call center data with blocking.Table 5.5 Initial experimental design for DigiPuppets.Table 5.6 Latin square design for DigiPuppets.Table 5.7 ANOVA on Latin square for DigiPuppets.Table 5.8 Standard form for Latin square design.Table 5.9 Another orthogonal Latin square design.Table 5.10 A bad choice for a Latin square design.Table 5.11 Randomizing a Latin square design: assign random numbers to rows a...Table 5.12 Data for new product example.Table 5.13 Latin square for background music exposure.Table 5.14 ANOVA results for distance1 (left) and distance2 (right).Table 5.15 ANOVA on combined distances.Table 5.16 Control and treatment means for various sample sizes.

      5 Chapter 6Table 6.1 ANOVA table for car rental data.Table 6.2 Regression results on car rental data.Table 6.3 Simple experiment.Table 6.4 Numeric data for Table 6.3.Table 6.5 Regression results for simple experiment with dummy variables.Table 6.6 Regression results for simple experiment with effect‐coded variable...Table 6.7

table of responses to factors
and
.Table 6.8 Response to interest rate and annual fee.Table 6.9 Effect coding vs. dummy coding.Table 6.10 Results of regressions on effect coding, dummies, and interactions...Table 6.11 Mnemonics for remembering level effect coding.Table 6.12 Design matrix for loan experiment.Table 6.13 Regression with all interactions, loan experiment.Table 6.14 Design matrix for credit card case.Table 6.15 Model matrix for credit card case.Table 6.16 Effects for credit card data set.Table 6.17 Regression results for credit card model.Table 6.18 Predictions (fitted values) for credit card model.

      6 Chapter 7Table 7.1 Postcard data.Table 7.2 Full factorial regression coefficients for postcard experiment.Table 7.3 Postcard regression, reduced model.Table 7.4 Choosing

, and
for main effects.Table 7.5 Are interactions consistent with main effects?.Table 7.6 Design matrix and predictions.Table 7.7 Postcard regression results, with replication.Table 7.8 Replicated postcard predictions with and without
.Table 7.9 Standard order for
design.Table 7.10 Factors for email campaign.Table 7.11

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