1. Analysis: Commercials at the Royal Theater Ken Chapman, Ph. D. K & C consultants: Complex Solutions to Simple Problems

2. Agenda  Legal Issues Background The Case for Fraud  Measuring Public Opinion Survey Goals Survey Results  Strategy Public Perceptions Possible Strategies Conclusions & Recommendations 1/28/2016 2

3. Background  Royal Theater Patron (Tommy) Dissatisfied 20 minutes of commercials  Allegation of fraud on Royal Theater’s part  Threatens to file class action lawsuit. 1/28/20163 Presenter: K. Chapman

4. The Case for Fraud  Misrepresentation Vs. Fraud  Prima Facie Case for Fraud A representation was made The representation was false When made, the representation was known to be false The plaintiff relied on the representation The plaintiff REASONABLY relied on the representation The plaintiff suffered damage (economic loss) as a result 1/28/20164 Presenter: K. Chapman

5. Simple Issues  Assertion of Fact The ticket did mention a 1:00 start time  Knowledge of Falsity The theater knew the movie began at 1:20  Intent to deceive The theater made money from the ads 1/28/2016 5 Presenter: K. Chapman

6. Reliance  Actual Reliance Tommy made sure he was seated by 1 pm  Justifiable (Reasonable) Reliance Starting time specified in:  Newspaper ad  Marquee  Employee  Movie ticket General public knowledge 1/28/2016 6 Presenter: K. Chapman

7. Damage – Economic Loss  Damage resulting from reliance: 20 minutes of lost time Nominal Punitive Damages 1/28/2016 7 Presenter: K. Chapman

8. The Case for Fraud  Conclusion: First four elements easy to establish Difficulty establishing reasonable reliance and damage Tommy HAS A WEAK case for fraud. 1/28/2016 8 Presenter: K. Chapman

9. Class Action Law Suit  To participate, patrons must show Reasonable Reliance Economic Damages  Conclusion: Most patrons won’t sue Presenter: K. Chapman 9

10. The Main Issue: Customer Service  Tommy’s complaints He was lied to and forced to watch ads He didn’t like the movie  Customer Service Send the customer away happy  Refund  Apology  Coupon  Outcome: No Lawsuit, No bad word of mouth.

11. How many patrons resent the ads?  Your reputation depends on your patron’s opinions of this behavior.  Objective – estimate the percentage of all theater patrons resenting commercials. If less than 10% resent the commercials: Don’t adjust the policy on commercials If 10% or more resent the commercials: Eliminate the commercials. 1/28/2016 11 Presenter: K. Chapman

12. Survey 1 Results  100 responses: 6% resent commercials. 95% confident that between 1.35% and 10.65% of moviegoers resent commercials. We can’t rule out the possibility that 10% or more of the population resents commercials. A bigger sample may be desirable 1/28/2016 12 Presenter: K. Chapman

13. Survey 2 Results  300 responses: 6% resent commercials 95% confident: The percentage of moviegoers who resent commercials is between 3.31% and 8.69% Strong evidence that less than 10% resent commercials Consortium’s rule: Take Tommy to Court 1/28/2016 13 Presenter: K. Chapman

14. Advertising & the Seating Period  Adjusting the seating period Eliminating the seating: The bad news  Less popcorn sales  Seating during the movie Distinguish between seating time and show time  Eliminate ads & keep the seating period 3.31-8.69% will like eliminating the ads Lost Advertising Revenues Some patrons will miss the ads 1/28/2016 14 Presenter: K. Chapman

15. Strategic Issues: The Whole Picture  Which customers resent commercials? Would they pay more for special shows? Can ads be made more entertaining?  Can upset customers be treated differently? A free ticket to a future show might have prevented a lawsuit 1/28/2016 15 Presenter: K. Chapman

16. Recommendations  Apologize to Tommy and offer some free tickets If he wants more, let him go to court.  Improve the accuracy of advertisements  Premium shows with fewer ads  Don’t let customers leave angry Training Refund money if customers leave early 1/28/2016 16 Presenter: K. Chapman

17. Questions?

18. Appendix Slides:  16-21: Sampling Error  22-26: Confidence Interval Calculations 1/28/2016 18

19. Hypothesis Testing Errors  Testing the population proportion: H 0 : Settlep >0.1 H 1 : Go to trialp <0.1

20. Risks of Taking Samples  Type I Error – Going to trial when the consortium should try to settle the case.  Type II Error – Avoiding going to trial by negotiating a settlement when the consortium should actually fight the case in court.  Larger survey sample sizes reduce the probability of both types of error. 1/28/2016 20

21. Estimating Confidence Interval for Population Proportion point estimate + margin of error

22. Factors Effecting Sampling Error  the sample size  the level of confidence  the estimated percentage of patrons who resent the ads. 1/28/2016 22

23. Sample Size and Confidence Level  The larger the sampling size, the smaller the error.  The greater the level of confidence, the larger the sampling error that must be tolerated.  With a fixed sample size, an increase in the level of confidence will increase the width of the interval. The wider the interval, the less precise is our estimate. 1/28/2016 23

24. Sample Proportion The further away the estimated percentage is from 50%, the smaller the sampling error. The sampling error is maximized when the estimated percentage who resent the ads is 50%. 24 1/28/2016 24

25. The 95% Confidence Interval 1/28/2016 25

26. Sample Proportion and 95% z 1/28/2016 26

27. Confidence Interval Calculation  1/28/2016 27

28. Confidence Interval Calculation  Interval is 1.35% - 10.65%.  With 95% confidence, the proportion of all movie patrons who resent commercials is between 1.35% and 10.65%. 1/28/2016 28