Two inference tasks
	    estimating a paramter
		1) get sample
		2) compute statistic from sample
		3) determine the quality of that statistic as an 
		     estimate for paramter
			a) confidence level
			b) confidence interval, margin of error

	    testing a hypothesis

	Video -- Against All Odds #23 (01:40 - 20:15)
		Woburn Leukemia, BLS stats, example computations

	Confidence Intervals for proportions
	    conditions under which the math applies
		1) parameter must have a fixed (unknown value) for population
		2) simple random sample or repeatable experiment
		3) sample includes 5 of each outcome
		4) population at least 10 times size of sample

	    the math:
		distribution of sample proportions (statistic) will be
			approximately normal N(p,root(p(1-p)/n)

		example: suppose fair coin (50% heads)
			flip it 100 times
			flip it 400 times
			flip it 1600 times

			for each:  ______% of time with _______
				   ______% of time between _____ and _____

		example: public opinion poll (suppose 30% rate)
			sample size 1500

	    unknown p, what do we do?
		note that (p)(1-p) < .25, so use .25	
		note that p-hat is usually very close to p, especially if
			the sample is large

		example: sample 1600 people and 500 people say yes
		
	 	example: Reeses' pieces

	Testing a hypothesis
		1) determine null and alternative hypotheses
		2) collect data 
		3) compute test statistic
			test stat is a measure of how true the 
			null hypothesis seems to be
		4) determine likelihood of such an extreme test 
			statistic if null hypothesis is true (p-value)
		5) make a decision

	Testing Hypotheses for Proportions
		test statistic is z-score

	    example: predicting election outcomes 


==

Monday, January 17
	Topic: More Inference for Proportions
	#Topic: Confidence Intervals
	#Topic: Hypothesis Testing for proportions
	#Topic: Chi-Squared & Hypothesis Testing 
	Read: Utts 21
	Read: Utts 22
	Due: HW #7 @ hw04.shtml

	Vocab: one-sided hypothesis test, two-sided hypothesis test,%%
	type 1 error, type 2 error, (power of a test)


	Hugo -- 13 times in 30 rolls; how unusual is that?
	    have students roll 30 dice several times and count number 
		of 6's rolled (work in pairs)