Presentation on theme: "Hypothesis Testing I 2/8/12 More on bootstrapping Random chance"— Presentation transcript:
1 Hypothesis Testing I 2/8/12 More on bootstrapping Random chance Null and alternative hypothesesRandomization distributionp-valueSection 4.1, 4.2Professor Kari Lock MorganDuke University
2 Announcements Homework 3 (due Monday) Research question and data for Project 1(proposal due next Wednesday)
3 Bootstrap CIOption 1: Estimate the standard error of the statistic by computing the standard deviation of the bootstrap distribution, and then generate a 95% confidence interval byOption 2: Generate a P% confidence interval as the range for the middle P% of bootstrap statistics
4 Suppose we have a random sample of 6 people: Patti
5 Original SamplePattiCreate a “sampling distribution” using this as our simulated population
6 Bootstrap Sample: Sample with replacement from the original sample, using the same sample size. PattiOriginal SampleBootstrap Sample
7 Continuous versus Discrete A continuous distribution can take any value within some range. The distribution will look like a smooth curve, without any gapsA discrete distribution only takes certain values. The distribution will be spiky, with gaps.ContinuousDiscrete
8 Criteria for Bootstrap CI Using the percentile method for a confidence interval bootstrapping for a confidence interval works for any statistic, as long as the bootstrap distribution isApproximately symmetricApproximately continuousUsing the standard error method also requiresApproximately bell-shapedAlways look at the bootstrap distribution to make sure these are true!
10 Number of Bootstrap Samples When using bootstrapping, you may get a slightly different confidence interval each time. This is fine!The more bootstrap samples you use, the more precise your answer will be.For the purposes of this class, 1000 bootstrap samples is fine. In real life, you probably want to take 10,000 or even 100,000 bootstrap samples
12 Paul the OctopusPaul the Octopus predicted 8 World Cup games, and predicted them all correctlyIs this evidence that Paul actually has psychic powers?How unusual would this be if he was just randomly guessing (with a 50% chance of guessing correctly)?How could we figure this out?
13 Coins and PaulDid you get all 8 heads?(a) Yes(b) No
14 10,000 Simulations www.lock5stat.com/statkey If Paul is just guessing, the chance of him getting all 8 correct is 4/1000.
15 HypothesesNull Hypothesis, H0 : Claim that there is no effect or no differenceAlternative Hypothesis, Ha : Claim that we seek evidence for, usually that there is some effectHypotheses are always given in terms of population parametersPaul the Octopus:H0 : 50% chance of correctly predicting each gameHa : >50% chance of correctly predicting each game
16 Paul the OctopusIn the case of Paul the Octopus, what type of parameter are we interested in?(Hint: Are there one or two variables?Are the variable(s) categorical or quantitative?)(a) Proportion(b) Mean(c) Difference in proportions(d) Difference in means(e) CorrelationPaul the Octopus:H0 : 50% chance of correctly predicting each gameHa : >50% chance of correctly predicting each game
17 Paul the Octopus Ha : p > 1/2 Let p denote the proportion of games that Paul guesses correctly (of all games he may have predicted)H0 : p = 1/2Ha : p > 1/2
18 HypothesesThe alternative hypothesis is supported by finding evidence (data) that contradicts the null hypothesis (and supports the alternative hypothesis)Data can only contradict or not contradict the null hypothesis, but can never confirm it
19 Alternative Hypothesis HypothesesNull HypothesisAlternative HypothesisUsually the null is a very specific statement, and so straightforward to assess evidence againstALL POSSIBILITIES
20 Paul and HypothesesH0 : p = 1/2Ha : p > 1/2What if Paul had gotten 4 out of 8 correct? What would you conclude?H0 is trueHa is trueH0 is falseHa is falseNothing
21 Your Own HypothesesCome up with a situation where you want to establish a claim based on dataWhat parameter(s) are you interested in?What would the null and alternative hypotheses be?What type of data would lead you to believe the null hypothesis is probably not true?
22 Measuring Evidence against H0 To see if a statistic provides evidence against H0, we need to see what kind of sample statistics we would observe, just by random chance,if H0 were true
24 Randomization Distribution A randomization distribution is the distribution of sample statistics we would observe, just by random chance, if the null hypothesis were trueSimulate many randomizations, assuming H0 is true, calculate the sample statistic each time, and collect these together to form a distribution
26 p-value We calculate this from a randomization distribution The p-value is the probability of getting a statistic as extreme (or more extreme) as that observed, just by random chance, if the null hypothesis is trueWe calculate this from a randomization distribution
28 p-valueWhat kinds of statistics would we get, just by random chance, if the null hypothesis were true? (randomization distribution)What proportion of these statistics are as extreme as our original sample statistic?(p-value)
29 Exercise and PulseDoes just 5 seconds of exercise raise your pulse rate?Let’s find out!How can we answer this question?