Understanding Statistics					 J.R. Rasmussen


					Class 8 Outline

I) Take home quiz 1: Turn in; we will go over on Wednesday


II) Last Class:  Statistical inference: New York times poll

	A) We read the New York times poll 

	B) Drew the picture: real world/theoretical world

	C) We viewed a poll results as a binomial distribution
		1) The single trial. Pr(success)=Pr(favor), n=the size of our sample
		2) assumed Pr(favor)=.40, we polled a sample of size 100
		
	D) Example: we sampled 100 people to see who they are going to vote for
		1) Binomial set up:  Pr(favor)=.40
		2) expected number of successes
		3) looked at 40 ± 10
		4) group exercise: we did one poll, and reported
		5) repeated until we had about 100 observations
			a) I kept track of frequency: the event E ( that our result is between 30 and 50)
		6) we calculated the relative frequency that we were
		between 30 and 50.  It was about  0.96-0.98
		7) group exercise: looked at the experimental results and then we did 10000 polls of 100 					residents.
		8)  then we calculated the relative frequencies
		9) the relative frequency was about 96.5%

III) Statistical inference: New York times poll  continued

	A) Group exercise: generating the N.Y. Times poll with n=979
		1) recall our poll is modeled as a binomial distribution with n=the size of the poll and with Pr(s)=.4
		2) how to calculate the proportion of the sample
	3) students generate 125 on Excel (put in a1:a125)
		 
	

III) Statistical inference: New York times poll  continued
		4) find proportion in b1:b125, double click the lower right corner of b1
		5) set up bins: .35, .355, .36, .365, ... .45 in d1:d21
		6) use histogram in data analysis and input the bins range and choose chart output
		7) everyone look at the histograms; get up and move around
		8) Now do 10000
			a) recalculate proportion in b1:b10000
			b) recalculate frequency
			c) get up and look at the histograms
		9) calculate the relative frequencies of being between .37 and .43:  students report
		10) Summary of what we have done and seen
IV) BREAK
	
V) Introduction to the normal distribution

	A) Why we need to learn about
	B) General comments about probabilities under a curve
	C) The bell shaped curve
		1) the normal(0,1) curve and its table
		2) How we use the table: examples
			a)Pr(Z { 2)
			b) Pr(Z } 1.2)
			c) Pr(-2.5 { Z { 1.2)
			d) Pr(-2 { Z {  2)
		3) Other normal curves and how we calculate
			a) normal curve with "mu"=2.5 and "sigma"=3
			b) how we convert to the standard normal curve
			c) example: X be normal with "mu"=2.5 and "sigma"=3
				i) pr(X {= 5) and pr(1 { X { 6)
		4) normal curves on Excel

VI) Assignment 4 due Wednesday 2/08/12