Stat 217 – Day 14Previously – Normal DistributionKissing CouplesLast Time – Sampling Distribution of Sample ProportionActivity 13-3 (handout)Activity 13-3Slide 7Slide 8Stat 217 – Day 14Applying the Central Limit TheoremPreviously – Normal DistributionActivity 12-6Always include sketch or screen captureAlways label horizontal axis Compare to 508356/4112052 = .1236Kissing CouplesHow often do you think kissing couples turn to the right?Suppose you thought it was 50/50 but you found a sample result of 64.5%, would this convince you that kissing couples in the entire population tend to turn right more than left?Need to know how sample proportions behave to know whether this is a surprising outcomeHow much random sampling variabilityLast Time – Sampling Distribution of Sample ProportionSimulation Took lots and lots of samples, of the same size, from the same population, and looked at the distribution of the sample proportion (p-hat)Central Limit Theorem (p. 259)1. When shape will be approximately normal2. The mean of the sample proportions will equal the value of the population proportion 3. The standard deviation equalsn)1(Activity 13-3 (handout)(a) proportion of all kissing couples that turn right, (b) Initially assuming =.5(c) statistic, p-hat = .64580.645Activity 13-3(e) Central Limit Theorem1. The distribution will be approximately normal2. With mean equal to .5 (since that is what we think equals)3. And standard deviation .0449Z = (.645 - .5)/.0449 = 3.23simulated sample proportions who turn to right (theta = 2/ 3)Frequency0.770.730.690.650.610.570.5380706050403020100simulated sample proportion who turn to right (theta = 3/ 4)Frequency0.8370.7970.7570.7170.6770.6370.5979080706050403020100To Turn in with Partner:Activity 15-1Answer to (f) is .1562For ThursdayLab 4Pre-lab for Lab 5By MondayActivity 15-2Self-check Activity
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