Stat 321 – Day 11AnnouncementsWhat to ExpectSome things to look out forStop and Think QuestionsDay 8, Ex 2: Randomized ResponseExample 2: Randomized ResponseSlide 8Stat 321 – Day 11ReviewAnnouncementsExam ThursdayReview sheet on webReview problems and solutions on webCovering chapters 1, 2; HW 1-3; Lab 1-3; Quiz 1-2You will be supplied with formulas (sample online)You will be allowed to bring in one page of notesBring your calculatorWhat to ExpectCalculation and Communicationshow steps (some only set up, partial credit)what does it mean, interpretationDon’t forget about Ch. 1Possibleconstruct an example where…show this relationship is true…prove this statement…Rework quizzes, hws; review labs (big ideas)Some things to look out forLanguageFrequency vs. relative frequencyProbability vs. empirical probabilityEstimated vs. exactSee Day 9 handout online for common confusionsPermutations vs. CombinationsMutually exclusive vs. independenceBayes’ Theorem vs. Law of Total ProbabilityStop and Think QuestionsIf you were to flip a coin six times, which sequence do you think would be most likely: HHHHHH or HHTHTH or HHHTTT?Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in antinuclear demonstrations. Which of the following events do you think is more likely? Explain your answer.A={Linda is a bank teller} B={Linda is a bank teller and is active in the feminist movement} Evelyn Marie Adams won the New Jersey lottery twice in a short time period. Her winnings were $3.9 million the first time and $1.5 million the second time. The New York Times claimed that the odds of one person winning the top price twice were about 1 in 17 trillion. How would you explain to someone that this is not a startling coincidence?Day 8, Ex 2: Randomized ResponseTechnique for asking sensitive questionsRandomly decide which question respondents will answer: sensitive or boringWork backwards with probability rules to estimate proportions for sensitive questionExample 2: Randomized ResponseFlip fair coinHeads: answer sensitive questionTails: answer boring question=“does your home phone number end in even digit?”Determine proportion of “yeses”Define eventsY=“response is yes”S=“respondent answered sensitive question”Example 2: Randomized ResponseRespondents are ensured confidentialityCan still obtain estimate for