Stat 217 – Day 10Last TimeComments on HW 2Slide 4Slide 5Slide 6Slide 7Lab 2 Notes (model online)Lab 2 NotesSlide 10Challenge QuestionLab 3About Exam 1Some advice for studyingSome advice during examSome big, big ideasActivity 4-19: Voter Turnout (p. 70)Slide 18Questions?Stat 217 – Day 10ReviewLast Time Judging “spread” of a distribution“Empirical rule”: In a mound-shaped symmetric distribution, roughly 68% of observations fall within one standard deviation of the mean, 95% within two standard deviations of the mean2SD = width of middle 68% of distributionZ-scores measure the relative position of an observation and provide us a unitless measuring stick for how far an observation falls from meanVery useful for comparing values from different distributionsBoxplots – visual display of five number summaryHelpful for comparing distributions (spread, center)Comments on HW 2Problem 2: Identify termsSampling frame is the list of the population used to select the sampleDoes not include the response variable information!(b) average number of words on a page of a textbook(d) tend to gain an average of 15 lbs?Comments on HW 2Act 5-14: Studies from Blink(a) and (b) only had response variables, observational studies(c) and (d) had 2 variables and the explanatory variable was randomly assigned, experimentsSo in (c) and (d) can potentially draw cause and effect conclusions“Generalizability” means can you take information from sample and apply it to the larger population? “There was not a significance difference in SAT performance in the sample so I don’t think there is in the population as well”Yes if have random sample, so maybe only in (a)Comments on HW 2Question 4: Hand hold(b) Can the status of the EV be determined by Ashleigh?Gender of participant vs. gender of researcherRandom sampling vs. random assignmentComments on HW 2Cause and effect vs. generalizing to populationYes NoYesNoWere groups randomly assigned?Were obs units randomly selected?Can draw cause-and-effect conclusionsCan generalize to larger populationComments on HW 2Question 5: AIDS testingMost of you got the table right but then read the wrong proportion from the tableOf those who tested positive, what proportion had AIDS = 4885/78515 = .062Of those who have AIDS, what proportion test positive= 4885/5000 = .977 (sensitivity)Positive test Negative test TotalCarries AIDS virus (2) 4885 (2) 115 (1) 5000Does not carry AIDS (3)73630 (3) 921370 (1) 995,000Total (4) 78515 (4) 921485 1,000,000Lab 2 Notes (model online)Comparing groupsAre people yawning a lot vs. does the yawn seed group yawn more oftenOverall proportion vs. Difference in conditional proportions 4.4% vs. 4.4 percentage pointsYawned “a lot more” vs. “yawned a lot more often”Interpreting p-value vs. conclusions from p-valueProbably want to explicitly compare p-value to some cut-offLab 2 NotesInterpretation of p-valueIf those subjects were going to yawn, regardless of which condition they were in, how often would the random assignment process alone lead to such a large difference in the conditional proportions?Each dot represents one (fake) random assignmentObservation units = 1000 fake random assignmentsVariable = difference in conditional proportionsRoughly 51% of fake random assignments (null model) saw a difference at least this largeDon’t consider this a small p-value since > .05Lab 2 NotesEffect of sample sizeChallenge QuestionWhy was “random assignment” used in the study?Why did we shuffle the cards and deal them into 2 groups?Lab 3 Randomization distributionIf everyone was going to remember the same number of letters regardless of which sequence they got, how often would the random assignment process alone lead to such a big difference in the group means?Each dot represents one random assignmentObservation units = 1000 fake random assignmentsVariable = difference in group meansWhere is the observed difference in means in this distribution?About Exam 150 minutes, 50 pointsWill include one of the self-check activitiesBring calculator, pencil, eraserCould be asked to use Minitab and/or to interpret Minitab outputNo cell phone calculators (square root)One 8.5x11 sheet of own notesBoth sides okI will supply paperSome advice for studyingReview handout, problems onlineSee also p. 627?Review lecture notes, text, hws, labsSee me for old homework, inclass activitiesWork problemsStart with ideas that we have emphasized more oftenSome advice during examIf you get stuck on a problem, move onlater parts, later problemsTry to hit the highlights in your answer (e.g., not all sources of bias, just the most serious)Be succinct (think before you write)Read the question carefullyShow all of your work, explain wellcommunication pointsRead entire question before writing anythingSome big, big ideasObservational units, variableRandom assignment vs. random samplingImplementationPurposeConsequence (Scope of conclusions)What see in sample vs. saying something beyond the sampleStatistic vs. ParameterStatistical significanceInterpretations, reasoningProperties, “what if” questions…How are you deciding this?Activity 4-19: Voter Turnout (p. 70)Statistic: .682 proportion claiming to voteParameter: .490 proportion claiming to voteWhat are some possible explanations for why these values differ?Those in sample do not represent populationThose in sample were not honestStatistics vary from sample to sample and may differ from parameter by chanceWhich of these explanations can we eliminate?No longer believe it was just “by