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Cal Poly STAT 321 - Review

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Stat 321 – Lecture 28Quiz 7AnnouncementsQuick OverviewChapter 5Slide 6Chapter 6Chapter 7Quiz/Lab/Exam FeedbackFinal ExamAdvice?GameThanks…Slide 14Stat 321 – Lecture 28ReviewLast piece of advice:Keep in mind that 17% of statistics are made up on the spot.Quiz 7Wanted to show E( 2) ≠ 2E(X2) ≠ [E(X)]2Needed another way of finding E(X2)V(X) = E(X2) – [E(X)]2 but here know variance and expected value of the sample mean!XAnnouncementsLocation of finalCurrent course grade in BBReflects through HW 8 including one drop, Lab 6, Quiz 6 including 2 dropsQuick OverviewPopulationSampleProbabilityStatisticsWhat does “probability” mean?How do we calculate probabilities for different kinds of events?What are the common models?Describing a distribution of data/important summary featuresMaking inferences from data to the population/process (when valid?)Chapter 5Sampling DistributionsTo know what conclusions we can make from a sample statistic, we need to know about the “precision” and behavior of the sample statistic in many samplesThis allows us to assess where we think the population parameter might be/whether we have a surprising outcome for a particular conjecture about the populationChapter 5Sampling DistributionsDescribe shape, center, spreadIf possible, list out all possible samplesOtherwise, does the Central Limit Theorem apply?Means, Sums, Proportions (Binomial)Be able to calculate probabilities (e.g., Quiz 6)If notConsider using rules of expectation and variance (linear combinations)Consider simulating an empirical sampling distributionKnow how impacted by changes (e.g., n)Chapter 6Properties of estimatorsUnbiased?Finding expected value of discrete/continuous random variablesRules for expectation (linear functions, V(X) shortcut)Finding the formula for the variance using rules of varianceEvaluating simulation resultsDeriving an estimatorMethod of MomentsMaximum likelihoodChapter 7Confidence intervalsGeneral principleWhat “confidence” means (how relates to probability)Selecting which confidence interval formula to useJustifications behind the methodsInterpreting, making inferences based on intervalHow impacted by changes (e.g., n)Solving for desired sample sizePrediction interval for individual observationQuiz/Lab/Exam FeedbackBe careful with notation, know how to label graphs, calculationsWhat’s a number? What’s a random variable?Know the interpretation/principles behind the calculationsWork problems!Get something written down…Show workEmail questionsFinal ExamFormulas and tables provided (see formulas pages online)3 notes pages of your ownEmphasis on Ch. 5-7 but cumulative1/3, 1/3, 1/3See problem solving strategies onlineAdvice?Be prepared to think/explain/interpret  Do not just plug into formulas from text Understand, don’t memorize Organize notes for efficient retrieval of information Re-read Handouts, especially expository passages, “boxed” paragraphs Review sheets from first two exams Solutions from first two exams Chapters from text Review problems Re-work examples from handouts Re-work homework problems Re-work examples from text Re-work questions from previous exams Work additional exercises from textGameRandom variable or number?  S2sE(p-hat)X1+X2V(X1 +


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